WO2024212045A1 - Encoding method, decoding method, code stream, encoder, decoder, and storage medium - Google Patents

Abstract

Embodiments of the present application disclose an encoding method, a decoding method, a code stream, an encoder, a decoder, and a storage medium. The decoding method comprises: parsing a code stream, and determining a prediction node index value corresponding to a node to be decoded; determining a previous first decoded node of the node to be decoded in a current frame; determining a prediction node according to the prediction node index value and the first decoded node; on the basis of the first decoded node, carrying out local motion processing on a first angle parameter value of the prediction node, and determining a second angle parameter value of the prediction node; on the basis of the first angle parameter value or the second angle parameter value, determining geometric parameters of the prediction node; and on the basis of the geometric parameters, determining a geometric prediction value of the node to be decoded. The embodiments of the present application can improve the accuracy of inter-frame prediction, thereby being capable of improving the encoding and decoding efficiency of geometric information, and improving the encoding and decoding performance of the point cloud.

Description

Coding and decoding method, code stream, encoder, decoder and storage medium Technical Field

The embodiments of the present application relate to the field of point cloud encoding and decoding technology, and in particular, to an encoding and decoding method, a bit stream, an encoder, a decoder, and a storage medium.

Background Art

In the geometry-based point cloud compression (G-PCC) codec framework, the geometric information and attribute information of the point cloud are encoded separately. The geometry coding of G-PCC can be divided into octree-based geometry coding and prediction tree-based geometry coding. For the prediction tree-based geometry coding, it is necessary to first establish a prediction tree; then traverse each node in the prediction tree, and after determining the prediction mode of each node, predict the geometric position information of the node according to the prediction mode to obtain the prediction residual, and finally encode the parameters such as the prediction mode and prediction residual of each node to generate a binary code stream.

In the above encoding process, the current node can also use the inter-frame prediction mode to predict the geometric position information of the node. However, in the related art, when performing inter-frame prediction on the selected inter-frame candidate node, only the prior information of global motion is considered, which leads to poor prediction effect, reduces the accuracy of inter-frame prediction, and thus reduces the coding and decoding efficiency of geometric information.

Summary of the invention

The embodiments of the present application provide a coding and decoding method, a bit stream, an encoder, a decoder and a storage medium, which can improve the accuracy of inter-frame prediction, thereby improving the coding and decoding efficiency of geometric information and improving the coding and decoding performance of point clouds.

The technical solution of the embodiment of the present application can be implemented as follows:

In a first aspect, an embodiment of the present application provides a decoding method, which is applied to a decoder method including:

Parse the bitstream and determine the predicted node index value corresponding to the node to be decoded;

Determine a first decoded node before the node to be decoded in the current frame;

Determine a prediction node according to the prediction node index value and the first decoded node;

Based on the first decoded node, performing local motion processing on the first angle parameter value of the prediction node to determine the second angle parameter value of the prediction node;

Determining a geometric parameter of the prediction node based on the first angle parameter value or the second angle parameter value;

Based on the geometric parameters, a geometric prediction value of the node to be decoded is determined.

In a second aspect, an embodiment of the present application provides an encoding method, which is applied to an encoder, and the method includes:

Determine a first encoded node preceding a node to be encoded in a current frame;

Determine a first candidate node having at least one geometric parameter identical to that of the first encoded node in a reference frame, and determine at least one second candidate node in the reference frame based on the first candidate node;

Performing local motion processing on the angle parameter value of at least one candidate node among the at least one second candidate node to obtain at least one updated second candidate node;

Based on the first candidate node and at least one updated second candidate node, a geometric prediction value of the node to be encoded is determined.

In a third aspect, an embodiment of the present application provides a code stream, wherein the code stream is generated by bit encoding according to information to be encoded; wherein the information to be encoded includes at least one of the following:

The geometric prediction residual value, quantization parameter, prediction node index value, first identification information and second identification information of the node to be encoded;

The first identification information is used to indicate whether the node to be encoded uses an inter-frame prediction mode, and the second identification information is used to indicate whether the node to be encoded enables a local motion processing mode.

In a fourth aspect, an embodiment of the present application provides a decoder, the decoder comprising a decoding unit, a first determining unit and a first local motion processing unit; wherein,

The decoding unit is configured to parse the bitstream, determine the predicted node index value corresponding to the node to be decoded; and determine the first decoded node before the node to be decoded in the current frame;

The first determining unit is configured to determine a prediction node according to the prediction node index value and the first decoded node;

The first local motion processing unit is configured to process a first angle of the predicted node based on the first decoded node. The parameter value is subjected to local motion processing to determine a second angle parameter value of the prediction node;

The first determination unit is further configured to determine the geometric parameters of the predicted node based on the first angle parameter value or the second angle parameter value; and determine the geometric prediction value of the node to be decoded based on the geometric parameters.

In a fifth aspect, an embodiment of the present application provides a decoder, the decoder comprising a first memory and a first processor; wherein:

The first memory is configured to store a computer program that can be executed on the first processor;

The first processor is configured to execute a decoding method on the decoder side when running the computer program.

In a sixth aspect, an embodiment of the present application provides an encoder, the encoder comprising a second determination unit, a second local motion processing unit and a prediction unit; wherein,

The second determination unit is configured to determine a first coded node preceding the node to be coded in the current frame; and determine a first candidate node having at least one geometric parameter identical to the first coded node in the reference frame, and determine at least one second candidate node in the reference frame according to the first candidate node;

The second local motion processing unit is configured to perform local motion processing on the angle parameter value of at least one candidate node among the at least one second candidate node to obtain the updated at least one second candidate node;

The prediction unit is configured to determine a geometric prediction value of the node to be encoded based on the first candidate node and at least one updated second candidate node.

In a seventh aspect, an embodiment of the present application provides an encoder, the encoder comprising a second memory and a second processor; wherein:

The second memory is configured to store a computer program that can be executed on the second processor;

The second processor is configured to execute the encoding method on the encoder side when running the computer program.

In an eighth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a first processor, the computer program implements a decoding method on the decoder side, or when the computer program is executed by a second processor, the computer program implements a coding and decoding method on the encoder side.

An embodiment of the present application provides a coding and decoding method. On the decoder side, first, the decoder parses the bit stream to determine the predicted node index value corresponding to the node to be decoded; then, the decoder determines the first decoded node before the node to be decoded in the current frame; then, the decoder determines the predicted node based on the predicted node index value and the first decoded node; then, the decoder performs local motion processing on the first angle parameter value of the predicted node based on the first decoded node to determine the second angle parameter value of the predicted node; finally, the decoder determines the geometric parameters of the predicted node based on the first angle parameter value or the second angle parameter value; based on the geometric parameters, the geometric prediction value of the node to be decoded is determined.

On the encoder side, first, the encoder determines the first encoded node preceding the node to be encoded in the current frame; then, the encoder determines a first candidate node in the reference frame that has at least one geometric parameter identical to the first encoded node, and determines at least one second candidate node in the reference frame based on the first candidate node; then, the encoder performs local motion processing on the angle parameter value of at least one candidate node among the at least one second candidate node to obtain at least one updated second candidate node; finally, the encoder determines the geometric prediction value of the node to be encoded based on the first candidate node and the at least one updated second candidate node. In this way, the technical solution of the present application is mainly for optimizing the angle parameter value of the prediction node used for inter-frame prediction.

On the one hand, since the second angle parameter value is obtained after the first angle parameter value is processed by local motion, the second angle parameter value has the prior information of local motion compared with the first angle parameter value, thereby achieving a more refined prediction of the geometric information of the prediction node, thereby improving the accuracy of inter-frame prediction. On the other hand, by performing local motion processing on the angle parameter value of the prediction node, when the reconstructed geometric information of the node to be decoded is determined using the second angle parameter value of the prediction node, the accuracy of the geometric reconstruction of the node to be decoded can be improved, thereby improving the accuracy of inter-frame prediction, improving the encoding and decoding efficiency of the geometric information, and thus improving the encoding and decoding performance of the point cloud.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1A is a schematic diagram of a three-dimensional point cloud image;

FIG1B is a partial enlarged view of a three-dimensional point cloud image;

FIG2A is a schematic diagram of six viewing angles of a point cloud image;

FIG2B is a schematic diagram of a data storage format corresponding to a point cloud image;

FIG3 is a schematic diagram of a network architecture for point cloud encoding and decoding;

FIG4A is a schematic diagram of a composition framework of a G-PCC encoder;

FIG4B is a schematic diagram of a composition framework of a G-PCC decoder;

FIG5A is a schematic diagram of a low plane position in the Z-axis direction;

FIG5B is a schematic diagram of a high plane position in the Z-axis direction;

FIG6 is a schematic diagram of a node encoding sequence;

FIG. 7A is a schematic diagram of a plane identification information;

FIG7B is a schematic diagram of another type of planar identification information;

FIG8 is a schematic diagram of sibling nodes of a current node;

FIG9 is a schematic diagram of the intersection of a laser radar and a node;

FIG10 is a schematic diagram of neighborhood nodes at the same partition depth and the same coordinates;

FIG11A is a schematic diagram of a current node being located at a low plane position of a parent node;

FIG11B is a second schematic diagram of a current node being located at a low plane position of a parent node;

FIG11C is a third schematic diagram of a current node being located at a low plane position of a parent node;

FIG12A is a schematic diagram of a current node being located at a high plane position of a parent node;

FIG12B is a second schematic diagram of a current node being located at a high plane position of a parent node;

FIG12C is a third schematic diagram of a high plane position of a current node located at a parent node;

FIG13 is a schematic diagram of predictive coding of planar position information of a laser radar point cloud;

FIG14 is a schematic diagram of IDCM encoding;

FIG15 is a schematic diagram of coordinate transformation of a rotating laser radar to obtain a point cloud;

FIG16 is a schematic diagram of predictive coding in the X-axis or Y-axis direction;

FIG17A is a schematic diagram showing an angle of predicting an X-plane by using a horizontal azimuth angle;

FIG17B is a schematic diagram showing an angle of the Y plane predicted by the horizontal azimuth angle;

FIG18 is another schematic diagram of predictive coding in the X-axis or Y-axis direction;

FIG19A is a schematic diagram of three intersection points included in a sub-block;

FIG19B is a schematic diagram of a triangular facet set fitted using three intersection points;

FIG19C is a schematic diagram of upsampling of a triangular face set;

FIG20 is a schematic diagram of the structure of a geometric prediction tree inter-frame encoding and decoding;

FIG21 is a schematic diagram of a flow chart of a decoding method provided in an embodiment of the present application;

FIG22 is a schematic diagram of a flow chart of an encoding method provided in an embodiment of the present application;

FIG23 is a schematic diagram of the structure of a geometric information inter-frame encoding and decoding provided in an embodiment of the present application;

FIG24 is a schematic diagram of the structure of another geometric information inter-frame encoding and decoding provided in an embodiment of the present application;

FIG25 is a schematic diagram of the composition structure of a decoder provided in an embodiment of the present application;

FIG26 is a schematic diagram of a specific hardware structure of a decoder provided in an embodiment of the present application;

FIG27 is a schematic diagram of the structure of an encoder provided in an embodiment of the present application;

FIG28 is a schematic diagram of a specific hardware structure of an encoder provided in an embodiment of the present application;

FIG. 29 is a schematic diagram of the composition structure of a coding and decoding system provided in an embodiment of the present application.

DETAILED DESCRIPTION

In order to enable a more detailed understanding of the features and technical contents of the embodiments of the present application, the implementation of the embodiments of the present application is described in detail below in conjunction with the accompanying drawings. The attached drawings are for reference only and are not used to limit the embodiments of the present application.

Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

In the following description, reference is made to “some embodiments”, which describe a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

It should also be pointed out that the terms "first\second\third" involved in the embodiments of the present application are only used to distinguish similar objects and do not represent a specific ordering of the objects. It can be understood that "first\second\third" can be interchanged in a specific order or sequence where permitted, so that the embodiments of the present application described here can be implemented in an order other than that illustrated or described here.

Point Cloud is a three-dimensional representation of the surface of an object. Point cloud (data) on the surface of an object can be collected through acquisition equipment such as photoelectric radar, lidar, laser scanner, and multi-view camera.

A point cloud is a set of irregularly distributed discrete points in space that express the spatial structure and surface properties of a three-dimensional object or scene. FIG1A shows a three-dimensional point cloud image and FIG1B shows a partial magnified view of the three-dimensional point cloud image. It can be seen that the point cloud surface is composed of densely distributed points.

In a two-dimensional image, each pixel has information and is distributed regularly, so there is no need to record its position information. However, the distribution of points in a point cloud in three-dimensional space is random and irregular, so it is necessary to record the position of each point in space. It can fully express a point cloud. Similar to a two-dimensional image, each position in the acquisition process has corresponding attribute information, usually RGB color value, which reflects the color of the object; for point clouds, in addition to color information, the attribute information corresponding to each point is also commonly the reflectance value, which reflects the surface material of the object. Therefore, point cloud data usually includes the position information of the point and the attribute information of the point. Among them, the position information of the point can also be called the geometric information of the point. For example, the geometric information of the point can be the three-dimensional coordinate information of the point (x, y, z). The attribute information of the point can include color information and/or reflectivity, etc. For example, reflectivity can be one-dimensional reflectivity information (r); color information can be information on any color space, or color information can also be three-dimensional color information, such as RGB information. Here, R represents red (Red, R), G represents green (Green, G), and B represents blue (Blue, B). For another example, color information can be brightness and chromaticity (YCbCr, YUV) information. Among them, Y represents brightness (Luma), Cb (U) represents blue color difference, and Cr (V) represents red color difference.

For a point cloud obtained according to the principle of laser measurement, the points in the point cloud may include the three-dimensional coordinate information of the points and the reflectivity value of the points. For another example, for a point cloud obtained according to the principle of photogrammetry, the points in the point cloud may include the three-dimensional coordinate information of the points and the three-dimensional color information of the points. For another example, a point cloud obtained by combining the principles of laser measurement and photogrammetry may include the three-dimensional coordinate information of the points, the reflectivity value of the points and the three-dimensional color information of the points.

As shown in Figures 2A and 2B, a point cloud image and its corresponding data storage format are shown. Figure 2A provides six viewing angles of the point cloud image, and Figure 2B consists of a file header information part and a data part. The header information includes the data format, data representation type, the total number of point cloud points, and the content represented by the point cloud. For example, the point cloud is in the ".ply" format, represented by ASCII code, with a total number of 207242 points, and each point has three-dimensional coordinate information (x, y, z) and three-dimensional color information (r, g, b).

Point clouds can be divided into the following categories according to the way they are obtained:

Static point cloud: the object is stationary, and the device that obtains the point cloud is also stationary;

Dynamic point cloud: The object is moving, but the device that obtains the point cloud is stationary;

Dynamic point cloud acquisition: The device used to acquire the point cloud is in motion.

For example, point clouds can be divided into two categories according to their usage:

Category 1: Machine perception point cloud, which can be used in autonomous navigation systems, real-time inspection systems, geographic information systems, visual sorting robots, disaster relief robots, etc.

Category 2: Point cloud perceived by the human eye, which can be used in point cloud application scenarios such as digital cultural heritage, free viewpoint broadcasting, 3D immersive communication, and 3D immersive interaction.

Point clouds can flexibly and conveniently express the spatial structure and surface properties of three-dimensional objects or scenes. Point clouds are obtained by directly sampling real objects, so they can provide a strong sense of reality while ensuring accuracy. Therefore, they are widely used, including virtual reality games, computer-aided design, geographic information systems, automatic navigation systems, digital cultural heritage, free viewpoint broadcasting, three-dimensional immersive remote presentation, and three-dimensional reconstruction of biological tissues and organs.

Point clouds can be collected mainly through the following methods: computer generation, 3D laser scanning, 3D photogrammetry, etc. Computers can generate point clouds of virtual three-dimensional objects and scenes; 3D laser scanning can obtain point clouds of static real-world three-dimensional objects or scenes, and can obtain millions of point clouds per second; 3D photogrammetry can obtain point clouds of dynamic real-world three-dimensional objects or scenes, and can obtain tens of millions of point clouds per second. These technologies reduce the cost and time cycle of point cloud data acquisition and improve the accuracy of data. The change in the way point cloud data is acquired makes it possible to acquire a large amount of point cloud data. With the growth of application demand, the processing of massive 3D point cloud data encounters bottlenecks in storage space and transmission bandwidth.

For example, taking a point cloud video with a frame rate of 30 frames per second (fps) as an example, the number of points in each point cloud frame is 700,000, and each point has coordinate information xyz (float) and color information RGB (uchar). The data volume of a 10s point cloud video is about 0.7 million × (4Byte × 3 + 1Byte × 3) × 30fps × 10s = 3.15GB, where 1Byte is 10bit; and a 1280 × 720 two-dimensional video with a YUV sampling format of 4:2:0 and a frame rate of 24fps, the data volume of 10s is about 1280 × 720 × 12bit × 24fps × 10s ≈ 0.33GB, and the data volume of a 10s two-view three-dimensional video is about 0.33 × 2 = 0.66GB. It can be seen that the data volume of a point cloud video far exceeds that of a two-dimensional video and a three-dimensional video of the same length. Therefore, in order to better realize data management, save server storage space, and reduce the transmission traffic and transmission time between the server and the client, point cloud compression has become a key issue in promoting the development of the point cloud industry.

That is to say, since the point cloud is a collection of massive points, storing the point cloud will not only consume a lot of memory, but also is not conducive to transmission. There is also not enough bandwidth to support direct transmission of the point cloud at the network layer without compression. Therefore, the point cloud needs to be compressed.

At present, the point cloud coding framework that can compress point clouds can be the geometry-based point cloud compression (G-PCC) codec framework or the video-based point cloud compression (V-PCC) codec framework provided by the Moving Picture Experts Group (MPEG), or the AVS-PCC codec framework provided by AVS. The G-PCC codec framework can be used to compress the first type of static point clouds and the third type of dynamically acquired point clouds, which can be based on the point cloud compression test platform (Test Model Compression 13, TMC13), and the V-PCC codec framework can be used to compress the second type of dynamic point clouds, which can be based on the point cloud compression test platform (Test Model Compression 2, TMC2). Therefore, the G-PCC codec framework is also called point cloud codec TMC13, and the V-PCC codec framework is also called point cloud codec TMC2.

The embodiment of the present application provides a network architecture of a point cloud encoding and decoding system including a decoding method and an encoding method. FIG3 is a schematic diagram of a network architecture of a point cloud encoding and decoding provided by the embodiment of the present application. As shown in FIG3, the network architecture includes one or more electronic devices 13 to 1N and a communication network 01, wherein the electronic devices 13 to 1N can perform video interaction through the communication network 01. During the implementation process, the electronic device can be various types of devices with point cloud encoding and decoding functions. For example, the electronic device can include a mobile phone, a tablet computer, a personal computer, a personal digital assistant, a navigator, a digital phone, a video phone, a television, a sensor device, a server, etc., which is not limited by the embodiment of the present application. Among them, the decoder or encoder in the embodiment of the present application can be the above-mentioned electronic device.

Among them, the electronic device in the embodiment of the present application has a point cloud encoding and decoding function, generally including a point cloud encoder (ie, encoder) and a point cloud decoder (ie, decoder).

The following describes the related technologies by taking the G-PCC codec framework and the AVS codec framework as examples.

It can be understood that in the point cloud G-PCC encoding and decoding framework, for the point cloud data to be encoded, the point cloud data is first divided into multiple slices by slice division. In each slice, the geometric information of the point cloud and the attribute information corresponding to each point are encoded separately.

FIG4A shows a schematic diagram of the composition framework of a G-PCC encoder. As shown in FIG4A , in the geometric encoding process, the geometric information is transformed so that all point clouds are contained in a bounding box (Bounding Box), and then quantized. This step of quantization mainly plays a role in scaling. Due to the quantization rounding, the geometric information of a part of the point cloud is the same, so whether to remove duplicate points is determined based on parameters. The process of quantization and removal of duplicate points is also called voxelization. Then, the Bounding Box is divided into octrees or a prediction tree is constructed. In this process, arithmetic coding is performed on the points in the leaf nodes of the division to generate a binary geometric bit stream; or, arithmetic coding is performed on the intersection points (Vertex) generated by the division (surface fitting is performed based on the intersection points) to generate a binary geometric bit stream. In the attribute encoding process, after the geometric encoding is completed and the geometric information is reconstructed, color conversion is required first to convert the color information (i.e., attribute information) from the RGB color space to the YUV color space. Then, the point cloud is recolored using the reconstructed geometric information so that the uncoded attribute information corresponds to the reconstructed geometric information. Attribute encoding is mainly performed on color information. In the process of color information encoding, there are two main transformation methods. One is the distance-based lifting transform that relies on the level of detail (LOD) division, and the other is directly performing the region adaptive hierarchical transform (RAHT). Both methods will convert the color information from the spatial domain to the frequency domain, and obtain high-frequency coefficients and low-frequency coefficients through transformation. Finally, the coefficients are quantized and then the quantized coefficients are arithmetically encoded to generate a binary attribute bit stream.

FIG4B shows a schematic diagram of the composition framework of a G-PCC decoder. As shown in FIG4B , for the acquired binary bit stream, the geometric bit stream and the attribute bit stream in the binary bit stream are first decoded independently. When decoding the geometric bit stream, the geometric information of the point cloud is obtained through arithmetic decoding-reconstruction of the octree/reconstruction of the prediction tree-reconstruction of the geometry-coordinate inverse conversion; when decoding the attribute bit stream, the attribute information of the point cloud is obtained through arithmetic decoding-inverse quantization-LOD partitioning/RAHT-color inverse conversion, and the point cloud data to be encoded (i.e., the output point cloud) is restored based on the geometric information and attribute information.

It should be noted that, as shown in FIG. 4A or FIG. 4B , the current geometric coding of G-PCC can be divided into octree-based geometric coding (marked by a dotted box) and prediction tree-based geometric coding (marked by a dotted box).

For Octree geometry encoding (OctGeomEnc), the octree-based geometry encoding includes: first, coordinate transformation of the geometric information so that all point clouds are contained in a Bounding Box. Then quantization is performed. This step of quantization mainly plays a role of scaling. Due to the quantization rounding, the geometric information of some points is the same. Whether to remove duplicate points is determined based on parameters. The process of quantization and removal of duplicate points is also called voxelization. Next, the Bounding Box is continuously divided into trees (such as octrees, quadtrees, binary trees, etc.) in the order of breadth-first traversal, and the placeholder code of each node is encoded. In related technologies, a company proposed an implicit geometry division method. First, the bounding box of the point cloud is calculated. Assume that _dx > _dy > _dz , the bounding box corresponds to a cuboid. During geometric partitioning, binary tree partitioning will be performed based on the x-axis to obtain two child nodes. When the condition _dx = _dy > _dz is met, quadtree partitioning will be performed based on the x- and y-axes to obtain four child nodes. When the condition _dx = _dy = _dz is finally met, octree partitioning will be performed until the leaf node obtained by partitioning is a 1×1×1 unit cube. The partitioning will be stopped, and the points in the leaf node will be encoded to generate a binary code stream. In the process of binary tree/quadtree/octree partitioning, two parameters are introduced: K and M. Parameter K indicates the maximum number of binary tree/quadtree partitions before octree partitioning; parameter M is used to indicate that the minimum block side length corresponding to binary tree/quadtree partitioning is 2M. At the same time, K and M must meet the following conditions: Assuming d _max = max(d _x , _dy , d _z ), d _min = min(d _x , _dy , d _z ), parameter K satisfies: K ≥ d _max - d _min ; parameter M satisfies: M ≥ d _min . The reason why parameters K and M meet the above conditions is that in the current process of geometric implicit partitioning in G-PCC, the priority of partitioning is binary tree, quadtree and octree. When the node block size does not meet the conditions of binary tree/quadtree, the node will be partitioned by octree until it is divided into the smallest unit of leaf node. 1 × 1 × 1. The octree-based geometric information coding mode can effectively encode the geometric information of the point cloud by utilizing the correlation between adjacent points in space. However, for some relatively flat nodes or nodes with planar characteristics, the coding efficiency of the point cloud geometric information can be further improved by using plane coding.

Exemplarily, Fig. 5A and Fig. 5B provide a kind of plane position schematic diagram. Wherein, Fig. 5A shows a kind of low plane position schematic diagram in the Z-axis direction, and Fig. 5B shows a kind of high plane position schematic diagram in the Z-axis direction. As shown in Fig. 5A, (a), (a0), (a1), (a2), (a3) here all belong to the low plane position in the Z-axis direction. Taking (a) as an example, it can be seen that the four subnodes occupied in the current node are all located at the low plane position of the current node in the Z-axis direction, so it can be considered that the current node belongs to a Z plane and is a low plane in the Z-axis direction. Similarly, as shown in Fig. 5B, (b), (b0), (b1), (b2), (b3) here all belong to the high plane position in the Z-axis direction. Taking (b) as an example, it can be seen that the four subnodes occupied in the current node are located at the high plane position of the current node in the Z-axis direction, so it can be considered that the current node belongs to a Z plane and is a high plane in the Z-axis direction.

Further, taking (a) in FIG. 5A as an example, the efficiency of octree coding and plane coding is compared. FIG. 6 provides a schematic diagram of the node coding order, that is, the node coding is performed in the order of 0, 1, 2, 3, 4, 5, 6, and 7 as shown in FIG. 6. Here, if the octree coding method is used for (a) in FIG. 5A, the placeholder information of the current node is represented as: 11001100. However, if the plane coding method is used, first, an identifier needs to be encoded to indicate that the current node is a plane in the Z-axis direction. Secondly, if the current node is a plane in the Z-axis direction, the plane position of the current node needs to be represented; secondly, only the placeholder information of the low plane node in the Z-axis direction needs to be encoded (that is, the placeholder information of the four subnodes 0, 2, 4, and 6). Therefore, based on the plane coding method, only 6 bits need to be encoded to encode the current node, which can reduce the representation of 2 bits compared with the octree coding of the related art. Based on this analysis, plane coding has a more obvious coding efficiency than octree coding. Therefore, for an occupied node, if a plane encoding method is used for encoding in a certain dimension, it is first necessary to represent the plane identification (planarMode) and plane position (PlanePos) information of the current node in the dimension, and then encode the occupancy information of the current node based on the plane information of the current node. Exemplarily, FIG7A shows a schematic diagram of plane identification information. As shown in FIG7A, there is a low plane in the Z-axis direction; correspondingly, the value of the plane identification information is true (true) or 1, that is, planarMode_ _Z = true; the plane position information is a low plane (low), that is, PlanePosition_ _Z = low. FIG7B shows another schematic diagram of plane identification information. As shown in FIG7B, there is not a plane in the Z-axis direction; correspondingly, the value of the plane identification information is false (false) or 0, that is, planarMode_ _Z = false.

It should be noted that for PlaneMode_ _i : 0 means that the current node is not a plane in the i-axis direction, and 1 means that the current node is a plane in the i-axis direction. If the current node is a plane in the i-axis direction, then for PlanePosition_ _i : 0 means that the current node is a plane in the i-axis direction, and the plane position is a low plane, and 1 means that the current node is a high plane in the i-axis direction. Among them, i represents the coordinate dimension, which can be the X-axis direction, the Y-axis direction, or the Z-axis direction, so i = 0, 1, 2.

In the G-PCC standard, to determine whether a node meets the plane coding condition and when the node meets the plane coding condition, it is necessary to predictively code the plane identification and plane position information of the node.

In the embodiment of the present application, there are three judgment conditions for judging whether a node satisfies plane coding in the current G-PCC standard, which are described in detail one by one below.

1. Judge based on the plane probability of the node in each dimension.

(1) Determine the local area density of the current node (local_node_density);

(2) Determine the probability Prob(i) of the current node in each dimension.

When the local area density of the node is less than the threshold Th (for example, Th=3), the plane probability Prob(i) of the current node in the three coordinate dimensions is compared with the thresholds Th0, Th1 and Th2, where Th0<Th1<Th2 (for example, Th0=0.6, Th1=0.77, Th2=0.88). Eligible _i (i=0,1,2) can be used here to indicate whether plane coding is started in each dimension: Eligible _i =Prob(i)>=threshold.

It should be noted that the threshold is adaptively changed. For example, when Prob(0)>Prob(1)>Prob(2), the setting of Eligible _i is as follows:
Eligible ₀ =Prob(0)>=Th0;
Eligible ₁ =Prob(1)>=Th1;
Eligible ₂ =Prob(2)>=Th2 (1)

When Prob(1)>Prob(0)>Prob(2), the setting of Eligible _i is as follows:
Eligible ₀ =Prob(0)>=Th1;
Eligible ₁ =Prob(1)>=Th0;
Eligible ₂ =Prob(2)>=Th2 (2)

Here, the update of Prob(i) is as follows:
Prob(i) _new =(L×Prob(i)+δ(coded node))/L+1 (3)

Where L = 255; in addition, if the coded node is a plane, then δ(coded node) is 1; otherwise δ(coded node) is 0.

Here, the update of local_node_density is as follows:
local_node_density _new =local_node_density+4*numSiblings (4)

Wherein, local_node_density is initialized to 4, and numSiblings is the number of sibling nodes of the node. Exemplarily, FIG8 shows a schematic diagram of the sibling nodes of the current node. As shown in FIG8, the current node is a node filled with slashes, and the nodes filled with grids are sibling nodes, then the number of sibling nodes of the current node is 5 (including the current node itself).

Second, determine whether the current layer nodes meet the plane coding requirements based on the point cloud density of the current layer.

The density of the current layer points is used to determine whether to perform planar coding on the nodes of the current layer. Assuming that the number of points in the current point cloud to be coded is pointCount, the number of points reconstructed by the infer direct coding model (IDCM) coding is numPointCountRecon, and because the octree is encoded based on the order of breadth-first traversal, the number of nodes to be coded in the current layer can be obtained as nodeCount. Then, the judgment of whether to start planar coding in the current layer is assumed to be planarEligibleKOctreeDepth, specifically: planarEligibleK OctreeDepth＝(pointCount-numPointCountRecon)<nodeCount×1.3.

Among them, if (pointCount-numPointCountRecon) is less than nodeCount×1.3, then planarEligibleK OctreeDepth is true; if (pointCount-numPointCountRecon) is not less than nodeCount×1.3, then planarEligibleKOctreeDepth is false. In this way, when planarEligibleKOctreeDepth is true, all nodes in the current layer are plane-encoded; otherwise, all nodes in the current layer are not plane-encoded, and only octree coding is used.

3. Determine whether the current node meets the plane coding requirements based on the acquisition parameters of the lidar point cloud.

Figure 9 shows a schematic diagram of the intersection of a laser radar and a node. As shown in Figure 9, a node filled with a grid is simultaneously passed through by two laser beams (Laser), so the current node is not a plane in the vertical direction of the Z axis; a node filled with a slash is small enough that it cannot be passed through by two lasers at the same time, so the node filled with a slash may be a plane in the vertical direction of the Z axis.

Furthermore, for nodes that meet the plane coding conditions, the plane identification information and the plane position information may be predictively coded.

First, predictive coding of the plane identification information.

Here, only three context information are used for encoding, that is, the plane identification in each coordinate dimension is separately designed for context.

Secondly, predictive coding of plane position information.

It should be understood that for the encoding of non-lidar point cloud plane position information, the predictive encoding of the plane position information may include:

(a) Using the occupancy information of neighboring nodes to predict the plane position information of the current node, the plane position information is divided into three elements: predicted as a low plane, predicted as a high plane, and unpredictable;

(b) The spatial distance between the nodes at the same partition depth and the same coordinates as the current node and the current node: “near” and “far”;

(c) if the node at the same partition depth and the same coordinates as the current node is a plane, determine the plane position of the node;

(d) Coordinate dimension (i=0,1,2).

It should be noted that in an embodiment of the present application, after determining the spatial distance between the node at the same division depth and the same coordinates as the current node and the current node, if the spatial distance is less than a preset distance threshold, then the spatial distance can be determined to be "near"; or, if the spatial distance is greater than the preset distance threshold, then the spatial distance can be determined to be "far".

For example, FIG10 shows a schematic diagram of neighborhood nodes at the same division depth and the same coordinates. As shown in FIG10 , the bold large cube represents the parent node (Parent node), the small cube filled with a grid inside it represents the current node (Current node), and the intersection position (Vertex position) of the current node is shown; the small cube filled with white represents the neighborhood nodes at the same division depth and the same coordinates, and the distance between the current node and the neighborhood node is the spatial distance, which can be judged as "near" or "far"; in addition, if the neighborhood node is a plane, then the plane position (Planar position) of the neighborhood node is also required.

In this way, as shown in Figure 10, the current node is a small cube filled with a grid, then the neighboring node is searched for a small cube filled with white at the same octree partition depth level and the same vertical coordinate, and the distance between the two nodes is judged as "near" and "far", and the plane position of the reference node is referenced.

Further, in the embodiment of the present application, Figures 11A to 11C show a schematic diagram of a current node being located at a low plane position of a parent node. As shown in Figures 11A to 11C, Figures 11A, 11B, and 11C show three examples of the current node being located at a low plane position of a parent node. The specific description is as follows:

① If any of the child nodes 4 to 7 of the point fill node is occupied, and all the grid fill nodes are not occupied, it is very likely that there is a plane in the current node (filled with a slash), and the plane is located lower.

② If the child nodes 4 to 7 of the point filling node are not occupied, and any grid filling node is occupied, it is very likely that There is a plane in the front node (filled with diagonal lines), and the plane is located higher.

③ If the child nodes 4 to 7 of the point filling node are all empty nodes and the grid filling nodes are all empty nodes, the plane position cannot be inferred and is therefore marked as unknown.

④ If any of the child nodes 4 to 7 of the point fill node is occupied and any of the grid fill nodes is occupied, the plane position cannot be inferred at this time, so it is marked as unknown.

In an embodiment of the present application, Figures 12A to 12C show a schematic diagram of a current node being located at a high plane position of a parent node. As shown in Figures 12A to 12C, Figures 12A, 12B, and 12C show three examples of the current node being located at a high plane position of a parent node. The specific description is as follows:

① If any of the child nodes 4 to 7 of the grid fill node is occupied, and the point fill node is not occupied, it is very likely that there is a plane in the current node (filled with a slash), and the plane position is lower.

② If the child nodes 4 to 7 of the grid fill node are not occupied, and the point fill node is occupied, it is very likely that there is a plane in the current node (filled with a slash), and the plane position is higher.

③If the child nodes 4 to 7 of the grid fill node are all unoccupied, and the point fill node is unoccupied, the plane position cannot be inferred at this time, so it is marked as unknown.

④ If one of the child nodes 4 to 7 of the grid fill node is occupied and the point fill node is occupied, the plane position cannot be inferred at this time, so it is marked as unknown.

It should also be understood that, for the encoding of the laser radar point cloud plane position information, Figure 13 shows a schematic diagram of predictive encoding of the laser radar point cloud plane position information. As shown in Figure 13, when the laser radar emission angle is θ _bottom , it can be mapped to the bottom plane (Bottom virtual plane); when the laser radar emission angle is θ _top , it can be mapped to the top plane (Top virtual plane).

That is to say, the plane position of the current node is predicted by using the laser radar acquisition parameters, and the position of the current node intersecting with the laser ray is used to quantify the position into multiple intervals, which is finally used as the context information of the plane position of the current node. The specific calculation process is as follows: Assuming that the coordinates of the laser radar are (xLidar, yLidar, zLidar), and the geometric coordinates of the current node are (x, y, z), then first calculate the vertical tangent value tanθ of the current node relative to the laser radar, and the calculation formula is as follows:

Furthermore, because each Laser has a certain offset angle relative to the LiDAR, it is also necessary to calculate the relative tangent value tanθ _corr,L of the current node relative to the Laser. The specific calculation is as follows:

Finally, the relative tangent value tanθ _corr,L of the current node is used to predict the plane position of the current node. Specifically, assuming that the tangent value of the lower boundary of the current node is tan(θ _bottom ), and the tangent value of the upper boundary is tan(θ _top ), the plane position is quantized into 4 quantization intervals according to tanθ _corr,L , that is, the context information of the plane position is determined.

However, the octree-based geometric information coding mode only has an efficient compression rate for points with correlation in space. For points in isolated positions in geometric space, the use of the direct coding model (DCM) can greatly reduce the complexity. For all nodes in the octree, the use of DCM is not represented by flag information, but is inferred from the parent node and neighbor information of the current node. There are three ways to determine whether the current node is eligible for DCM encoding, as follows:

(1) The current node has no sibling child nodes, that is, the parent node of the current node has only one child node, and the parent node of the parent node of the current node has only two occupied child nodes, that is, the current node has at most one neighbor node.

(2) The parent node of the current node has only one child node, the current node. At the same time, the six neighbor nodes that share a face with the current node are also empty nodes.

(3) The number of sibling nodes of the current node is greater than 1.

Exemplarily, FIG14 provides a schematic diagram of IDCM coding. If the current node does not have the DCM coding qualification, it will be divided into octrees. If it has the DCM coding qualification, the number of points contained in the node will be further determined. When the number of points is less than a threshold value (for example, 2), the node will be DCM-encoded, otherwise the octree division will continue. When the DCM coding mode is applied, it is first necessary to encode whether the current node is a true isolated point, that is, IDCM_flag. When IDCM_flag is true, the current node is encoded using DCM, otherwise octree coding is still used. When the current node satisfies the DCM coding, the DCM coding mode of the current node needs to be encoded. There are currently two DCM modes, namely: (a) only one point exists (or multiple points, but they are repeated points); (b) contains two points. Finally, the geometric information of each point needs to be encoded. Assuming that the side length of the node is ^2d , d bits are required to encode each component of the geometric coordinates of the node, and the bit information is directly encoded into the bit stream. It should be noted here that when encoding the LiDAR point cloud, the coordinate information of the three dimensions is predicted by using the LiDAR acquisition parameters. Measurement coding can further improve the coding efficiency of geometric information.

Furthermore, the IDCM encoding process is described in detail below.

When the current node meets the DCM encoding mode, first encode the number of points numPoints of the current node; encode the number of points of the current node according to different DirectModes:

(1) If the current node does not meet the requirements of the DCM node, it will exit directly (that is, the number of points is greater than 2 points and it is not a duplicate point).

(2) If the number of points numPonts contained in the current node is less than or equal to 2, the encoding process is as follows:

i) First encode whether the numPonts of the current node is greater than 1;

ii) If the current node has only one point and the geometry coding environment is geometry lossless coding, it is necessary to encode that the second point of the current node is not a duplicate point.

(3) If the number of points numPonts contained in the current node is greater than 2, the encoding process is as follows:

i) First encode the numPonts of the current node to be less than or equal to 1;

ii) Secondly, it is encoded that the second point of the current node is a repeated point, and then it is encoded whether the number of repeated points of the current node is greater than 1. When the number of repeated points is greater than 1, it is necessary to perform exponential Golomb decoding on the remaining number of repeated points.

After encoding the number of points in the current node, the coordinate information of the points contained in the current node is encoded. The following will introduce the lidar point cloud and the human eye point cloud in detail.

(A) Point cloud facing the human eye.

(1) If the current node contains only one point, the geometric information of the point in three dimensions will be directly encoded (Bypass coding);

(2) If the current node contains two points, the priority coded coordinate axis dirextAxis will be obtained first by using the geometric coordinates of the points. It should be noted here that the coordinate axes currently compared only include the x-axis and the y-axis, but not the z-axis. Assuming that the geometric coordinates of the current node are nodePos, the judgment method is as follows:
dirextAxis=! (nodePos[0]<nodePos[1])

That is, the axis with the smaller node coordinate geometry position will be used as the priority coded axis dirextAxis, and then the geometry information of the priority coded axis dirextAxis will be encoded as follows. Assume that the bit depth of the coded geometry corresponding to the priority coded axis is nodeSizeLog2, and assume that the coordinates of the two points are pointPos[0] and pointPos[1]. The specific encoding process is as follows:

After the encoding of the first-coded coordinate axis dirextAxis is completed, the geometric coordinates of the current node are directly encoded. Assuming that the remaining encoding bit depth of each point is nodeSizeLog2, the specific encoding process is as follows:
for(int axisIdx＝0; axisIdx<3; ++axisIdx)
for(int mask＝(1<<nodeSizeLog2[axisIdx])>>1;mask;mask>>1)
encodePosBit(!!(pointPos[axisIdx]&mask)).

(ii) Towards LiDAR point cloud.

If the current node contains two points, the priority coded coordinate axis dirextAxis will be obtained first by using the geometric coordinates of the points. Assuming that the geometric coordinates of the current node are nodePos, the judgment method is as follows:
dirextAxis=! (nodePos[0]<nodePos[1])

That is, the axis with the smaller node coordinate geometry position will be used as the priority coded axis dirextAxis. It should be noted that the currently compared coordinate axes only include the x-axis and the y-axis, but not the z-axis. Secondly, the priority coded coordinate axis dirextAxis geometry information is first encoded as follows, assuming that the priority coded axis corresponds to the coded geometry bit depth of nodeSizeLog2, and assuming that the coordinates of the two points are pointPos[0] and pointPos[1]. The specific encoding process is as follows:

After encoding the priority-encoded coordinate axis dirextAxis, the geometric coordinates of the current node are encoded.

Since the laser radar point cloud can obtain the acquisition parameters of the laser radar point cloud, the geometric coordinate information of the current node can be predicted, so as to further improve the efficiency of the geometric information encoding of the point cloud. Similarly, the geometric information nodePos of the current node is first used to obtain a directly encoded main axis direction, and then the geometric information of the encoded direction is used to predict the geometric information of another dimension. Also, assuming that the axis direction of the direct encoding is directAxis, and assuming that the bit depth of the direct encoding is nodeSizeLog2, the encoding method is as follows:
for(int mask＝(1<<nodeSizeLog2)>>1;mask;mask>>1)
encodePosBit(!!(pointPos[directAxis]&mask)).

It should be noted here that all geometric accuracy information in the directAxis direction will be encoded here.

Exemplarily, FIG15 provides a schematic diagram of coordinate transformation for obtaining point clouds using a rotating laser radar. In the Cartesian coordinate system, the (x, y, z) coordinates of each node can be converted to (R, φ, i). In addition, the laser scanner can perform laser scanning at a preset angle, and different θ(i) can be obtained under different values of i. For example, when i is equal to 1, θ(1) can be obtained, and the corresponding scanning angle is -15°; when i is equal to 2, θ(2) can be obtained, and the corresponding scanning angle is -13°; when i is equal to 10, θ(10) can be obtained, and the corresponding scanning angle is +13°; when i is equal to 9, θ(19) can be obtained, and the corresponding scanning angle is +15°.

In this way, after encoding all the precisions of the directAxis coordinate direction, the LaserIdx corresponding to the current point, i.e., the pointLaserIdx number in Figure 15, will be calculated first, and the LaserIdx of the current node, i.e., nodeLaserIdx, will be calculated; secondly, the LaserIdx of the node, i.e., nodeLaserIdx, will be used to predictively encode the LaserIdx of the point, i.e., pointLaserIdx, where the calculation method of the LaserIdx of the node or point is as follows. Assuming that the geometric coordinates of the point are pointPos, the starting coordinates of the laser ray are LidarOrigin, and assuming that the number of Lasers is LaserNum, the tangent value of each Laser is tanθ _i , and the offset position of each Laser in the vertical direction is _Zi , then:

After calculating the LaserIdx of the current point, the LaserIdx of the current node is first used to predict the pointLaserIdx of the point. After the LaserIdx of the current point is encoded, the three-dimensional geometric information of the current point is predicted and encoded using the acquisition parameters of the laser radar.

For example, FIG16 shows a schematic diagram of predictive coding in the X-axis or Y-axis direction. As shown in FIG16 , a box filled with a grid represents a current node, and a box filled with a slash represents an already coded node. Here, the LaserIdx corresponding to the current node is first used to obtain the corresponding predicted value of the horizontal azimuth, that is, Secondly, the node geometry information corresponding to the current point is used to obtain the horizontal azimuth angle corresponding to the node Assuming the geometric coordinates of the node are nodePos, the horizontal azimuth The calculation method between the node geometry information is as follows:

By using the acquisition parameters of the laser radar, we can get the number of rotation points of each Laser, which is the number of points obtained when each laser ray rotates one circle. Then, we can use the number of rotation points of each Laser to calculate the rotation angular velocity of each Laser. deltaPhi is calculated as follows:

Furthermore, using the horizontal azimuth angle of the node And the horizontal azimuth of the previous Laser code point corresponding to the current point Calculate the predicted horizontal azimuth angle corresponding to the current point That is, the predicted values of the horizontal azimuth angles as shown in Figures 17A and 17B. Figure 17A shows a schematic diagram of predicting the angle of the Y plane through the horizontal azimuth angle, and Figure 17B shows a schematic diagram of predicting the angle of the X plane through the horizontal azimuth angle. Here, for the predicted value of the horizontal azimuth angle corresponding to the current point The calculation is as follows:

For example, FIG18 shows another schematic diagram of predictive coding in the X-axis or Y-axis direction. As shown in FIG18 , the portion filled with a grid (left side) represents the low plane, and the portion filled with dots (right side) represents the high plane. Indicates the horizontal azimuth of the low plane of the current node, Indicates the horizontal azimuth of the high plane of the current node, Indicates the predicted horizontal azimuth angle corresponding to the current node.

Thus, by using the predicted value of the horizontal azimuth and the low plane horizontal azimuth of the current node and the high plane horizontal azimuth To predict the geometric information of the current node. The details are as follows:


int context=(angLel≥0&&angLeR≥0)||(angLel<0&&angLeR<0)? 0:2;
int minAngle=std∷min(abs(angLel),abs(angLeR));
int maxAngle=std∷max(abs(angLel),abs(angLeR));
context+=maxAngle>minAngle? 0:1;
context+=maxAngle>minAngle? 0:4.

After the LaserIdx of the encoding point is completed, the LaserIdx corresponding to the current point will be used to predict the Z-axis direction of the current point. That is, the radius information radius of the radar coordinate system is calculated by using the x and y information of the current point. Then, the tangent value of the current point and the vertical offset are obtained by using the laser LaserIdx of the current point, and the predicted value of the Z-axis direction of the current point, namely Z_pred, can be obtained. The details are as follows:

int tanTheta=tanθ _laserIdx ;
int zOffset = Z _laserIdx ;
Z_pred=radius×tanTheta-zOffset.

Furthermore, Z_pred is used to perform predictive coding on the geometric information of the current point in the Z-axis direction to obtain the prediction residual Z_res, and finally Z_res is encoded.

It should be noted that when nodes are divided into leaf nodes, in the case of geometric lossless coding, the number of repeated points in the leaf nodes needs to be encoded. Finally, the placeholder information of all nodes is encoded to generate a binary code stream. In addition, G-PCC currently introduces a plane coding mode. In the process of geometric division, it will determine whether the child nodes of the current node are in the same plane. If the child nodes of the current node meet the conditions of the same plane, the child nodes of the current node will be represented by the plane.

For octree-based geometric decoding, the decoding end follows the order of breadth-first traversal. Before decoding the placeholder information of each node, it will first use the reconstructed geometric information to determine whether the current node is to be plane decoded or IDCM decoded. If the current node meets the conditions for plane decoding, the plane identification and plane position information of the current node will be decoded first, and then the placeholder information of the current node will be decoded based on the plane information; if the current node meets the conditions for IDCM decoding, it will first decode whether the current node is a true IDCM node. If it is a true IDCM decoding, it will continue to parse the DCM decoding mode of the current node, and then the number of points in the current DCM node can be obtained, and finally the geometric information of each point will be decoded. For nodes that do not meet either plane decoding or DCM decoding, the placeholder information of the current node will be decoded. By continuously parsing in this way, the placeholder code of each node is obtained, and the nodes are continuously divided in turn until the division is stopped when a 1×1×1 unit cube is obtained, the number of points contained in each leaf node is obtained by parsing, and finally the geometric reconstructed point cloud information is restored.

The following is a detailed introduction to the IDCM decoding process.

Similar to the processing at the encoding end, the prior information is first used to determine whether the node starts IDCM. That is, the starting conditions of IDCM are as follows:

(1) The current node has no sibling child nodes, that is, the parent node of the current node has only one child node, and the parent node of the parent node of the current node has only two occupied child nodes, that is, the current node has at most one neighbor node.

(2) The parent node of the current node has only one child node, the current node. At the same time, the six neighbor nodes that share a face with the current node are also empty nodes.

(3) The number of sibling nodes of the current node is greater than 1.

Furthermore, when a node meets the conditions for DCM coding, first decode whether the current node is a real DCM node, that is, IDCM_flag; when IDCM_flag is true, the current node adopts DCM coding, otherwise it still adopts octree coding.

Next, decode the number of points numPoints of the current node. The specific decoding method is as follows:

i) First decode whether numPonts of the current node is greater than 1;

ii) If the numPonts of the current node is greater than 1, continue decoding to see if the second point is a duplicate point; if the second point is not a duplicate point, it can be implicitly inferred that the second type that satisfies the DCM mode contains only two points;

iii) If the numPonts of the current node obtained by decoding is less than or equal to 1, continue decoding to see if the second point is a repeated point; if the second point is not a repeated point, it can be implicitly inferred that the second type that satisfies the DCM mode contains only one point; if the second point obtained by decoding is a repeated point, it can be inferred that the third type that satisfies the DCM mode contains multiple points, but they are all repeated points, then continue decoding to see if the number of repeated points is greater than 1 (entropy decoding), and if it is greater than 1, continue decoding the number of remaining repeated points (decoding using exponential Columbus).

If the current node does not meet the requirements of the DCM node, it will exit directly (that is, the number of points is greater than 2 points and it is not a duplicate point).

After decoding the number of points in the current node, the coordinate information of the points contained in the current node is decoded. The following will introduce the lidar point cloud and the human eye point cloud in detail.

(A) Point cloud facing the human eye.

(1) If the current node contains only one point, the geometric information of the point in three dimensions will be directly decoded (Bypass coding);

(2) If the current node contains two points, the geometric coordinates of the points will be used to obtain the priority decoding coordinate axis dirextAxis. It should be noted that the coordinate axes currently compared only include the x and y axes, not the z axis. Assuming that the geometric coordinates of the current node are nodePos, the judgment method is as follows:
dirextAxis=! (nodePos[0]<nodePos[1]) (10)

That is, the axis with the smaller node coordinate geometry position will be used as the priority decoding axis dirextAxis, and then the priority decoding axis dirextAxis geometry information will be decoded first in the following way. Assume that the geometry bit depth to be decoded corresponding to the priority decoding axis is nodeSizeLog2, and assume that the coordinates of the two points are pointPos[0] and pointPos[1] respectively. The specific encoding process is as follows:

After decoding the priority axis dirextAxis, the geometric coordinates of the current point are directly decoded. Assuming that the remaining encoding bit depth of each point is nodeSizeLog2, and assuming that the coordinate information of the point is pointPos, the specific decoding process is as follows:

(ii) Towards LiDAR point cloud.

If the current node contains two points, the geometric coordinates of the points will be used to obtain the priority decoding axis dirextAxis. Assuming that the geometric coordinates of the current node are nodePos, the judgment method is as follows:
dirextAxis=! (nodePos[0]<nodePos[1]) (11)

That is, the axis with the smaller node coordinate geometry position will be used as the priority decoding axis dirextAxis. It should be noted that the currently compared coordinate axes only include the x-axis and the y-axis, but not the z-axis. Secondly, the priority encoded coordinate axis dirextAxis geometry information is first decoded as follows, assuming that the priority decoded axis corresponds to the code geometry bit depth of nodeSizeLog2, and assuming that the coordinates of the two points are pointPos[0] and pointPos[1]. The specific encoding process is as follows:

After decoding the priority coordinate axis dirextAxis, decode the geometric coordinates of the current point.

Similarly, we first use the geometric information nodePos of the current node to get a main axis direction for direct decoding, and then use the geometric information of the decoded direction to decode the geometric information of another dimension. Assuming that the axis direction for direct decoding is directAxis, and assuming that the bit depth to be decoded in direct decoding is nodeSizeLog2, the decoding method is as follows:

It should be noted here that all geometric accuracy information in the directAxis direction will be decoded here.

After decoding all the precisions of the directAxis coordinate direction, the LaserIdx of the current node, i.e., nodeLaserIdx, is calculated first; secondly, the LaserIdx of the node, i.e., nodeLaserIdx, is used to predict and decode the LaserIdx of the point, i.e., pointLaserIdx. The calculation method of the LaserIdx of the node or point is the same as that of the encoder. Finally, the LaserIdx of the current point and the predicted residual information of the LaserIdx of the node are decoded to obtain ResLaserIdx. The decoding method is as follows:
PointLaserIdx＝nodeLaserIdx+ResLaserIdx (12)

After decoding the LaserIdx of the current point, the three-dimensional geometric information of the current point is predicted and decoded using the acquisition parameters of the laser radar. The specific algorithm is as follows:

As shown in Figure 11, first use the LaserIdx corresponding to the current point to obtain the corresponding predicted value of the horizontal azimuth, that is, Secondly, the node geometry information corresponding to the current point is used to obtain the horizontal azimuth angle corresponding to the node Assuming the geometric coordinates of the node are nodePos, the horizontal azimuth The calculation method between the node geometry information is as follows:

By using the acquisition parameters of the laser radar, we can get the number of rotation points of each Laser, numPoints, which represents the number of points obtained when each laser ray rotates one circle. Then, we can use the number of rotation points of each Laser to calculate the rotation angular velocity deltaPhi of each Laser. The calculation method is as follows:

Furthermore, using the horizontal azimuth angle of the node And the horizontal azimuth of the previous Laser code point corresponding to the current point Calculate the predicted horizontal azimuth angle corresponding to the current point That is, the predicted value of the horizontal azimuth angle as shown in Figures 17A and 17B. The calculation method is as follows:

Thus, by using the predicted value of the horizontal azimuth and the low plane horizontal azimuth of the current node and the horizontal azimuth of the high plane To predict and decode the geometric information of the current node. The details are as follows:


int context=(angLel≥0&&angLeR≥0)||(angLel<0&&angLeR<0)? 0:2;
int absAngleL＝abs(angLel);
int absAngleR=abs(angLeR);
context+=absAngleL>absAngleR? 0:1;
context+=maxAngle>minAngle<<1?4:0.

After decoding the LaserIdx of the completed point, the Z-axis direction of the current point will be predicted and decoded using the LaserIdx corresponding to the current point, that is, the radius information radius of the radar coordinate system is calculated by using the x and y information of the current point, and then the tangent value of the current point and the vertical offset are obtained using the laser LaserIdx of the current point, so that the predicted value of the Z-axis direction of the current point, namely Z_pred, can be obtained. The details are as follows:

int tanTheta=tanθ _laserIdx ;
int zOffset = Z _laserIdx ;
Z_pred=radius×tanTheta-zOffset.

Furthermore, the decoded Z_res and Z_pred are used to reconstruct and restore the geometric information of the current point in the Z-axis direction.

For geometric information coding based on triangle soup (trisoup), in the geometric information coding framework based on trisoup, geometric division must also be performed first, but different from geometric information coding based on binary tree/quadtree/octree, this method does not need to divide the point cloud into unit cubes with a side length of 1×1×1 step by step, but stops dividing when the side length of the sub-block is W. Based on the surface formed by the distribution of the point cloud in each block, the surface and the twelve edges of the block are obtained. The vertex coordinates of each block are encoded in turn to generate a binary code stream.

For point cloud geometry information reconstruction based on trisoup, when point cloud geometry information reconstruction is performed at the decoding end, the vertex coordinates are first decoded to complete the triangle patch reconstruction, and the process is shown in Figures 19A, 19B, and 19C. Among them, there are three intersection points (v1, v2, v3) in the block shown in Figure 19A. The triangle patch set formed by these three intersection points in a certain order is called triangle soup, i.e., trisoup, as shown in Figure 19B. Afterwards, sampling is performed on the triangle patch set, and the obtained sampling points are used as the reconstructed point cloud in the block, as shown in Figure 19C.

For Predictive geometry coding (PredGeomTree), the Predictive geometry coding includes: first, sorting the input point cloud. The currently used sorting methods include unordered, Morton order, azimuth order, and radial distance order. At the encoding end, the prediction tree structure is established by using two different methods, including: KD-Tree (high-latency slow mode) and low-latency fast mode (using laser radar calibration information). When using the laser radar calibration information, each point is divided into different Lasers, and the prediction tree structure is established according to different Lasers. Next, based on the structure of the prediction tree, each node in the prediction tree is traversed, and the geometric position information of the node is predicted by selecting different prediction modes to obtain the prediction residual, and the geometric prediction residual is quantized using the quantization parameter. Finally, through continuous iteration, the prediction residual of the prediction tree node position information, the prediction tree structure, and the quantization parameters are encoded to generate a binary code stream.

For geometric decoding based on the prediction tree, the decoding end reconstructs the prediction tree structure by continuously parsing the bit stream, and then obtains the geometric position prediction residual information and quantization parameters of each prediction node through parsing, and dequantizes the prediction residual to recover the reconstructed geometric position information of each node, and finally completes the geometric reconstruction of the decoding end.

After the geometric encoding is completed, the geometric information needs to be reconstructed. At present, attribute encoding is mainly performed on color information. First, the color information is converted from the RGB color space to the YUV color space. Then, the point cloud is recolored using the reconstructed geometric information so that the unencoded attribute information corresponds to the reconstructed geometric information. In color information encoding, there are two main transformation methods, one is the distance-based lifting transformation that relies on LOD division, and the other is to directly perform RAHT transformation. Both methods will convert color information from the spatial domain to the frequency domain, and obtain high-frequency coefficients and low-frequency coefficients through transformation. Finally, the coefficients are quantized and encoded to generate a binary code stream, as shown in Figures 4A and 4B.

Furthermore, when using geometric information to predict attribute information, the Morton code can be used to search for the nearest neighbor. The Morton code corresponding to each point in the point cloud can be obtained from the geometric coordinates of the point. The specific method for calculating the Morton code is described as follows. For each component of the three-dimensional coordinate represented by a d-bit binary number, its three components can be expressed as:

Among them, x _l ,y _l ,z _l ∈{0,1} are the binary values corresponding to the highest bit (l=1) to the lowest bit (l=d) of x, y, z respectively. The Morton code M is x, y, z starting from the highest bit, and then arranged in sequence from x _l ,y _l ,z _l to the lowest bit. The calculation formula of M is as follows:

Where, _ml′∈ {0,1} is the value of the highest bit (l′＝1) to the lowest bit (l′＝3d) of M. After the Morton code M, the points in the point cloud are arranged in ascending order according to the Morton code, and the weight value w of each point is set to 1.

It can also be understood that for the G-PCC codec framework, the general test conditions are as follows:

(1) There are 4 test conditions:

Condition 1: The geometric position is limitedly lossy and the attributes are lossy;

Condition 2: The geometric position is lossless, but the attributes are lossy;

Condition 3: The geometric position is lossless, and the attributes are limitedly lossy;

Condition 4: The geometric position and attributes are lossless.

(2) The general test sequences include four categories: Cat1A, Cat1B, Cat3-fused, and Cat3-frame. The Cat2-frame point cloud only contains reflectance attribute information, the Cat1A and Cat1B point clouds only contain color attribute information, and the Cat3-fused point cloud contains both color and reflectance attribute information.

(3) Technical routes: There are 2 types, which are distinguished by the algorithm used for geometric compression.

Technical route 1: Octree encoding branch.

At the encoding end, the bounding box is divided into sub-cubes in sequence, and the non-empty sub-cubes (containing points in the point cloud) are divided again until the leaf node obtained by division is a 1×1×1 unit cube. In the case of geometric lossless coding, the number of points contained in the leaf node needs to be encoded, and finally the encoding of the geometric octree is completed to generate a binary code stream.

At the decoding end, the decoding end obtains the placeholder code of each node by continuously parsing in the order of breadth-first traversal, and continuously divides the nodes in turn until a 1×1×1 unit cube is obtained. In the case of geometric lossless decoding, it is necessary to parse the number of points contained in each leaf node and finally restore the geometrically reconstructed point cloud information.

Technical route 2: prediction tree encoding branch.

At the encoding end, the prediction tree structure is established by using two different methods, including: based on KD-Tree (high-latency slow mode) and using lidar calibration information (low-latency fast mode). Using lidar calibration information, each point can be divided into different Lasers, and the prediction tree structure is established according to different Lasers. Next, based on the structure of the prediction tree, each node in the prediction tree is traversed, and the geometric position information of the node is predicted by selecting different prediction modes to obtain the prediction residual, and the geometric prediction residual is quantized using the quantization parameter. Finally, through continuous iteration, the prediction residual of the prediction tree node position information, the prediction tree structure, and the quantization parameters are encoded to generate a binary code stream.

At the decoding end, the decoding end reconstructs the prediction tree structure by continuously parsing the bit stream, and then obtains the geometric position prediction residual information and quantization parameters of each prediction node through parsing, and dequantizes the prediction residual to restore the reconstructed geometric position information of each node, and finally completes the geometric reconstruction at the decoding end.

In a possible implementation manner, the following specifically describes the geometric prediction tree inter-frame encoding and decoding in the related art.

Taking Figure 15 as an example, the point coordinates of the point cloud input are (x, y, z). Using the prior radar information of the current point cloud, the position information of the point cloud is converted into the radar coordinate system (radius, laserIdx). Assuming the geometric coordinates of the point are pointPos, the starting coordinates of the laser ray are LidarOrigin, and assuming the number of lasers is LaserNum, the tangent value of each Laser is tanθ _i , and the offset position of each Laser in the vertical direction is _Zi , the calculation method of the node or point LaserIdx is as follows:

Furthermore, assuming that the geometric coordinates of the node are pointPos, the horizontal azimuth The calculation of is as follows:

Furthermore, the depth information radius is calculated as follows:

Among them, LidarOrigin is generally 0.

For example, FIG20 shows a schematic diagram of a geometric information inter-frame coding and decoding structure. As shown in FIG20, the current point to be coded in the current frame is filled with a grid, and the current point is represented by a at the previous coded node; there is a first reference frame and a second reference frame. Frames, wherein the first reference frame may be a previous frame of the current frame, and the second reference frame may be a global motion compensation (Global Motion Compensation, GMC) reference frame.

Thus, taking FIG. 20 as an example, when inter-frame prediction coding is performed on the current point to be coded, the previous coded node a of the current point to be coded in the prediction tree is traversed;

In the first reference frame (i.e., the previous reference frame), find the node a that has the same and node b of laserID, taking points c and d encoded or decoded after point b in the first reference frame as inter-frame candidate points;

In the second reference frame (i.e., the reference frame of the previous frame after global motion), find the node a that has the same and laserID point g, and use the points e and f encoded or decoded after point g in the second reference frame as inter-frame candidate points; at the same time, point e and point f Replaced by the parent node of the current point to be encoded

Then, different prediction points (including several intra-frame candidate points and up to 4 inter-frame candidate points) are selected through rate distortion optimization (RDO) to predict the geometric position information of the node to obtain the prediction residual, and the geometric prediction residual is quantized using the quantization parameter. Finally, through continuous iteration, the prediction mode, prediction residual, prediction tree structure, quantization parameter and other parameters of the prediction tree node position information are encoded to generate a binary code stream.

At the decoding end, the decoding end continuously parses the bitstream, reconstructs the prediction tree structure, and traverses the prediction tree to find the previous decoded node a before the current point to be decoded;

First, the prediction mode is decoded; if the prediction mode is inter-frame prediction mode, the prediction point is selected from the following at most four candidate points using the decoded prediction mode:

In the first reference frame (i.e., the previous reference frame), find the node a that has the same and node b of laserID, taking points c and d encoded or decoded after point b in the first reference frame as inter-frame candidate points;

In the second reference frame (i.e., the reference frame of the previous frame after global motion), find the node a that has the same and laserID point g, and use the points e and f encoded or decoded after point g in the second reference frame as inter-frame candidate points; at the same time, point e and point f Replaced by the parent node of the current point to be decoded

Secondly, the geometric position prediction residual information and quantization parameters of different prediction points are obtained by analysis, and the prediction residual is dequantized, so that the reconstructed geometric position information of each node can be restored, and finally the geometric reconstruction at the decoding end is completed.

The following describes in detail a decoding method proposed in an embodiment of the present application in conjunction with the inter-frame prediction part.

A decoding method is provided in an embodiment of the present application. Referring to FIG. 21 , a flowchart of an optional decoding method provided in an embodiment of the present application is shown. As shown in FIG. 21 , the method may include:

S101, parsing a bitstream to determine a predicted node index value corresponding to a node to be decoded.

In the embodiment of the present application, after receiving the code stream transmitted by the encoder, the decoder parses the code stream to obtain the node index value of the node to be decoded.

It should be noted that the decoding method of the embodiment of the present application is applied to a decoder. In addition, the decoding method may refer to a point cloud inter-frame prediction method; or a method for decoding geometric information between point cloud frames, which mainly improves the inter-frame prediction algorithm in the relevant technology, and can perform local motion processing on the angle parameter value of the prediction node, so as to achieve a better inter-frame prediction effect.

In the embodiment of the present application, the node to be decoded is one of the points in the current frame.

It should also be noted that in the embodiment of the present application, in the point cloud, the point can be all points in the point cloud, or it can be part of the points in the point cloud, and these points are relatively concentrated in space. Here, the node to be decoded can specifically refer to the node currently to be decoded in the point cloud.

In the embodiments of the present application, the node to be decoded is also referred to as a point to be decoded, a current node, a current point, a current node to be decoded, a current point to be decoded, etc., and the present application does not limit this.

In an embodiment of the present application, the node to be decoded may be a point in the point cloud currently to be decoded, or the node to be decoded may include multiple points in the point cloud currently to be decoded, which is not limited in the present application.

It should be noted that, when the node to be decoded includes multiple points in the point cloud to be decoded currently, the multiple points included in the node to be decoded are repeated points. In this case, the node to be decoded includes multiple points having the same geometric prediction information.

In the embodiment of the present application, the predicted node index value may be a unique identifier of the node to be decoded.

In the embodiment of the present application, the preset node index value is a pre-set node index value, that is, the preset node index value is an index value specified or agreed upon by both the encoder and the decoder.

In the embodiment of the present application, the preset node index value includes at least one node index value corresponding to at least one reference frame. In other words, the preset node index value specifies which reference frame the node index value belongs to.

That is, the decoder can determine the node to be decoded from multiple decoded nodes in the reference frame according to the predicted node index value of the node to be decoded, wherein the multiple decoded nodes in the reference frame are candidate nodes for the predicted node.

Exemplarily, the multiple decoded nodes in the reference frame are: decoded node c, decoded node d, decoded node e, decoded node f, decoded node m, decoded node n, decoded node o, decoded node p, etc. Among them, decoded node c The index value of is 0, the index value of the decoded node d is 1, the index value of the decoded node e is 2, the index value of the decoded node f is 3, the index value of the decoded node m is 4, the index value of the decoded node n is 5, the index value of the decoded node o is 6, and the index value of the decoded node p is 7. Assuming that the decoder determines that the predicted node index value corresponding to the node to be decoded is 3 by parsing the bitstream, the decoder can determine that the node to be decoded is the decoded node f.

In the embodiment of the present application, the predicted node index value may be a parameter written in a profile, or may be the value of a flag, which is not specifically limited here.

Exemplarily, taking flag as an example, flag can be set to a digital form. For example, when the value of flag is 0, it indicates that the node to be decoded is the decoding point corresponding to the predicted node index value 0 (such as node c). When the value of flag is 2, it indicates that the node to be decoded is the decoding point corresponding to the predicted node index value 2 (such as node e).

In the embodiment of the present application, the node index value can be represented in binary form. For example, the node index value 2 can be represented as 10, and the node index value 3 can be represented as 11. The node index value can also be represented in other base forms, which is not limited in the present application.

S102: Determine the first decoded node before the node to be decoded in the current frame.

In the embodiment of the present application, when the first decoded node preceding the node to be decoded in the current frame is determined, the geometric information (geometric position information) of the first decoded node is determined.

It should be noted that the first decoded node here refers to the geometric information of the first decoded node. That is to say, after determining the first decoded node before the node to be decoded in the current frame, the geometric information of the first decoded node in the point cloud is determined. The geometric information here can be understood as the position information of the first decoded node in the point cloud. For example, the geometric information of the first decoded node can be radar coordinate information or Cartesian coordinate information, etc., and this application does not impose any limitation on this.

It should also be noted that in the embodiment of the present application, the geometric parameters (geometric information) here refer to the parameters in the radar coordinate system. Among them, the geometric parameters may include: horizontal azimuth Radar laser index value laserID and depth information radius.

In an embodiment of the present application, when the geometric information of the first decoded node is radar coordinate information, the geometric information of the first decoded node at least includes an angle parameter corresponding to the first decoded node, that is, a third angle parameter value.

In the embodiment of the present application, the angle parameter value is the angle information of the horizontal position of the horizontal plane, that is,

In the embodiment of the present application, the third angle parameter value of the first decoded node is the angle information of the horizontal position of the first decoded node on the horizontal plane.

In an embodiment of the present application, the current frame is a frame where the current node to be decoded is located, and the current frame includes at least one point.

In an embodiment of the present application, the current frame is obtained by scanning a circle of the laser radar along the XY plane (horizontal plane), and the current frame may include multiple points.

In the embodiment of the present application, since the current frame is obtained by scanning a circle along the XY plane (horizontal plane) by the laser radar, each point contained in the current frame corresponds to the same radar index value, that is, corresponds to the same laser radar.

In this embodiment of the present application, the radar index value is the unique identification information of the laser radar.

In an embodiment of the present application, the first decoded node is a node that has been decoded before the node to be decoded in the current frame.

It should be noted that, in the embodiment of the present application, the first decoded node may also be any H decoded nodes before the node to be decoded in the current frame, where H is a positive integer greater than or equal to 1. For example, the first decoded node may be the two decoded nodes before the node to be decoded in the current frame, the first decoded node may also be the four decoded nodes before the node to be decoded in the current frame, etc., and the present application does not limit this.

In some embodiments of the present application, determining a first decoded node before a node to be decoded in a current frame may include:

Based on the decoding order of the prediction tree, a previous decoded node of the node to be decoded is determined, and the previous decoded node is used as the first decoded node.

In the embodiment of the present application, according to the decoding order of the prediction tree corresponding to the current frame, the previous decoded node of the node to be decoded is used as the first decoded node.

S103: Determine a prediction node according to the prediction node index value and the first decoded node.

In an embodiment of the present application, a predicted node is determined based on a predicted node index value corresponding to the node to be decoded and the first decoded node. It should be noted that after the predicted node is determined, the geometric information (i.e., geometric parameters) of the predicted node is determined.

In an embodiment of the present application, according to the third angle parameter value of the first decoded node, a decoded node corresponding to the predicted node index value is determined in at least one decoded node in the reference frame, and the decoded node corresponding to the predicted node index value is used as the predicted node.

In the embodiment of the present application, the predicted node is determined by the third angle parameter value of the first decoded node and the predicted node index value.

In the embodiment of the present application, the prediction node is also called a prediction node, a target node, a target point, etc., which is not limited in the embodiment of the present application.

In the embodiment of the present application, the prediction node may be a node in a reference frame other than the current frame, or a node in the current frame. Node.

In the embodiment of the present application, whether the predicted node is a node in a reference frame other than the current frame or a node in the current frame depends on the prediction mode of the node to be decoded, wherein the prediction mode may include an inter-frame prediction mode and an intra-frame prediction mode.

Exemplarily, when the prediction mode of the node to be decoded is the inter-frame prediction mode, the prediction node is a node in a reference frame other than the current frame; when the prediction mode of the node to be decoded is the intra-frame prediction mode, the prediction node is a node in a reference frame of the current frame.

S104 . Based on the first decoded node, perform local motion processing on the first angle parameter value of the prediction node to determine a second angle parameter value of the prediction node.

S105. Determine a geometric parameter of the prediction node based on the first angle parameter value or the second angle parameter value.

S106. Determine a geometric prediction value of the node to be decoded based on the geometric parameters.

In the embodiment of the present application, local motion processing is performed on the first angle parameter value of the predicted node according to the third angle parameter value of the first decoded node, so as to obtain the second angle parameter value of the predicted node.

In the embodiment of the present application, the first angle parameter value is an angle parameter value of the predicted node obtained according to the third angle parameter value of the first decoded node.

In the embodiment of the present application, the second angle parameter value is an angle parameter value obtained by performing local motion processing on the first angle parameter value.

In an embodiment of the present application, the geometric parameters of the predicted node include first geometric parameters and second geometric parameters; wherein the first geometric parameters include: depth information of the predicted node, radar index value of the predicted node and first angle parameter value; the second geometric parameters include: depth information of the predicted node, radar index value of the predicted node and second angle parameter value.

In some embodiments of the present application, S105 may include:

Determine the depth information of the prediction node, the radar index value of the prediction node, and the first angle parameter value as the geometric parameters of the prediction node; or,

The depth information of the prediction node, the radar index value of the prediction node, and the second angle parameter value are determined as the geometric parameters of the prediction node.

In an embodiment of the present application, after the prediction node is determined, the geometric parameter (eg, geometric position information) may be used as the geometric prediction value of the node to be decoded.

In the embodiment of the present application, the geometric parameters here refer to the parameters in the radar coordinate system. Among them, the geometric parameters may include: horizontal azimuth (i.e. angle parameter value), radar laser index value laserID and depth information radius of the predicted node.

In an embodiment of the present application, the geometric prediction value may be: depth information of the prediction node, radar index value of the prediction node, and a first angle parameter value; the geometric prediction value may also be: depth information of the prediction node, radar index value of the prediction node, and a second angle parameter value.

It can be understood that since the first angle parameter value is obtained after local motion processing to obtain the second angle parameter value, the second angle parameter value has the prior information of local motion compared to the first angle parameter value, thereby achieving a more refined prediction of the geometric information of the prediction node, thereby improving the accuracy of inter-frame prediction.

It can be understood that, since the second angle parameter value takes into account the prior information of local motion, when the reconstructed geometric information of the node to be decoded is determined using the second angle parameter value of the predicted node, the accuracy of the geometric reconstruction of the node to be decoded can be improved.

In an embodiment of the present application, the decoder first parses the code stream to determine the predicted node index value corresponding to the node to be decoded; then, the decoder determines the first decoded node before the node to be decoded in the current frame; then, the decoder determines the predicted node based on the predicted node index value and the first decoded node; then, the decoder performs local motion processing on the first angle parameter value of the predicted node based on the first decoded node to determine the second angle parameter value of the predicted node; finally, the decoder determines the geometric parameters of the predicted node based on the first angle parameter value or the second angle parameter value; based on the geometric parameters, the geometric prediction value of the node to be decoded is determined. Since the decoder performs local motion processing on the first angle parameter value of the predicted node to obtain the second angle parameter value, the second angle parameter value has prior information related to the local motion, which can improve the accuracy of inter-frame prediction, thereby improving the decoding efficiency of the geometric information of the point cloud and improving the decoding performance of the point cloud.

In some embodiments of the present application, S104 includes S1041 to S1042:

S1041. When the prediction node index value represents that the prediction node is a preset node, local motion information is determined based on the fourth angle parameter value of the second decoded node and the first angle parameter value of the prediction node; the fourth angle parameter value of the second decoded node is less than or equal to and closest to the third angle parameter value of the first decoded node; the second decoded node is determined based on the first decoded node in the reference frame where the prediction node is located.

In the embodiment of the present application, when the predicted node index value represents that the predicted node is a preset node, it is determined to perform local motion processing on the first angle parameter value of the predicted node corresponding to the predicted node index value.

In the embodiment of the present application, when the predicted node index value indicates that the predicted node is not a preset node, determining the predicted node The first angle parameter value of the prediction node corresponding to the index value is not subjected to local motion processing, and the first angle parameter value of the prediction node is directly used as the angle parameter value of the prediction node.

That is to say, only when the prediction node index value represents that the prediction node is a preset node, the decoder will perform local motion processing on the first angle parameter value of the prediction node to obtain the second angle parameter value; when the prediction node index value represents that the prediction node is not a preset node, the decoder does not need to perform local motion processing on the first angle parameter value of the prediction node, and can use the first angle parameter value as the second angle parameter value.

In the embodiment of the present application, the preset nodes are nodes specified or negotiated by both the decoder and the encoder. In other words, the preset nodes are pre-specified nodes for which local motion processing is performed.

Exemplarily, the decoder and the encoder agree to perform local motion processing on node e (index value is 2), node f (index value is 3), node o (index value is 6), and node p (index value is 7) in the first reference frame, that is, the preset nodes are node e, node f, node o, and node p. Assume that the prediction node index value of the prediction node is 6. At this time, the prediction node index value represents that the prediction node is node o in the preset nodes. At this time, the decoder performs local motion processing on the first angle parameter value of the prediction node (node o). Assume that the prediction node index value of the prediction node is 0. At this time, the prediction node index value represents that the prediction node is not a node in the preset nodes. At this time, the decoder does not perform local motion processing on the first angle parameter value of the prediction node (node c), and directly uses the first angle parameter value of the prediction node (node c) as the second angle parameter value of the prediction node.

In an embodiment of the present application, the decoder may perform local motion processing on the first angle parameter value of the predicted node to obtain the second angle parameter value only when the predicted node index value matches the preset node index value.

That is to say, when the predicted node index value matches the preset node index value, it is possible to not only know to which reference frame the predicted node corresponding to the predicted node index value belongs, but also to determine whether local motion processing is required for the first angle parameter value of the predicted node.

In the embodiment of the present application, the second decoded node is a decoded node in the reference frame. In addition, the fourth angle parameter value of the second decoded node is less than or equal to the third angle parameter value of the first decoded node.

In an embodiment of the present application, the second decoded node is a decoded node in the reference frame that has the same radar index as the first decoded node and whose angle parameter value of the first point is less than or equal to and closest to the angle parameter value of the first decoded node.

That is, the second decoded node is the first decoded node in the reference frame whose angle parameter value is less than or equal to the angle parameter value of the first decoded node.

Exemplarily, when the reference frame includes a decoded node c, a decoded node b, and a decoded node h, wherein the angle parameter value of the decoded node c is greater than the angle parameter value of the first decoded node, and the angle parameter value of the decoded node b and the angle parameter value of the decoded node h are both less than or equal to the angle parameter value of the first decoded node. However, the angle parameter value of the decoded node b is greater than the angle parameter value of the decoded node h. It can be seen that the decoded node b is the first decoded node whose angle parameter value is less than or equal to the angle parameter value of the first decoded node. In this way, the decoded node b is determined to be the second decoded node.

In an embodiment of the present application, the second decoded node and the first decoded node may have the same radar index, or the second decoded node and the first decoded node may have different radar indexes; the second decoded node and the first decoded node may have the same depth information, or the second decoded node and the first decoded node may have different depth information; the second decoded node and the first decoded node may have the same angle parameter value, or the second decoded node and the first decoded node may have different angle parameter values, and the present application does not limit this.

In the embodiment of the present application, the second decoded node is determined based on the angle parameter value of the first decoded node in the reference frame where the prediction node is located. In other words, the second decoded node is related to the third angle parameter value of the first decoded node.

In the embodiment of the present application, in the process of determining the predicted node according to the predicted node index value and the first decoded node, the fourth angle parameter value of the second decoded node has been determined.

Therefore, in the embodiment of the present application, the local motion information corresponding to the predicted node is determined according to the obtained target angle parameter value of the second decoded node and the first angle parameter value of the predicted node, wherein the local motion information represents the prior information after the first angle parameter value is locally moved.

In some embodiments of the present application, a difference value between a fourth angle parameter value of the second decoded node and a first angle parameter value of the predicted node is determined as local motion information.

In the embodiment of the present application, the difference between the fourth angle parameter value and the first angle parameter value may be used as local motion information.

In the embodiment of the present application, the difference between the fourth angle parameter value after being multiplied by the first weight and the first angle parameter value after being multiplied by the second weight may also be used as local motion information.

Exemplarily, the difference between the fourth angle parameter value and the first angle parameter value is used as the local motion information, which can be expressed as:
auto deltaPhi=interPred.second[1]-interPredPrev.second[1];

Wherein, deltaPhi represents the difference (difference value) between the fourth angle parameter value and the first angle parameter value, interPred.second[1] represents the first angle parameter value of the predicted node, and interPredPrev.second[1] represents the fourth angle parameter value of the second decoded node.

In some embodiments of the present application, the reference frame where the prediction node is located includes: a first reference frame and a second reference frame.

In some embodiments of the present application, the first reference frame is at least one frame obtained by performing global motion on the second reference frame.

In some embodiments of the present application, the second reference frame is a decoded frame that is K frames before the current frame, where K is an integer greater than 0.

In some embodiments of the present application, the preset node is at least one decoded node in the first reference frame except the second decoded node.

Exemplarily, the second decoded node in the first reference frame is node g, and the first reference frame, in addition to the second decoded node, also includes: node e, node f, node o, and node p. Then the preset node may be at least one of node e, node f, node o, and node p.

In some embodiments, the second reference frame may be a previous frame of the current frame; the first reference frame may be a previous frame of the previous frame of the current frame. For example, if the current frame is Frame t, the first reference frame may be Frame t-1, and the second reference frame may be Frame t-2; t is an integer.

It should also be noted that, in the embodiment of the present application, a third reference frame may also be included, and the number of reference frames and the number of candidate nodes are not specifically limited. In the embodiment of the present application, only the first reference frame and the second reference frame are used as examples for detailed description.

S1042. Determine a second angle parameter value of the prediction node based on the local motion information.

In the embodiment of the present application, the first angle parameter value is updated according to the local motion information of the prediction node to determine the second angle parameter value of the prediction node.

In the embodiment of the present application, when the predicted node index value represents that the predicted node is not a preset node, the first angle parameter value of the predicted node is used as the second angle parameter value. When the predicted node index value does not match the preset node index value, the decoder does not need to perform local motion processing on the first angle parameter value of the predicted node, and the first angle parameter value can be used as the second angle parameter value.

It should be noted that the predicted node index value represents that when the predicted node is not a preset node, the first angle parameter value of the predicted node is used as the second angle parameter value.

When the prediction node index value indicates that the prediction node is not a preset node, directly using the first angle parameter value as the second angle parameter value of the prediction node is a parallel solution with S104 and S105. The specific execution order needs to be determined according to the prediction node.

When the predicted node index value indicates that the predicted node is not a preset node, the first angle parameter value of the predicted node is used as the second angle parameter value, and the geometric parameter of the predicted node is determined according to the second angle parameter value.

Exemplarily, based on FIG. 23 , the decoder and the encoder agree to perform local motion processing on node e (index value 2), node f (index value 3), node o (index value 6), and node p (index value 7) in the first reference frame, that is, the preset nodes are node e, node f, node o, and node p. Assume that the predicted node index value of the predicted node is 0. At this time, the predicted node index value indicates that the predicted node is not a node in the preset nodes. At this time, the decoder does not perform local motion processing on the first angle parameter value of the predicted node (node c), and directly uses the first angle parameter value of the predicted node (node c) as the second angle parameter value of the predicted node.

It can be understood that since the second angle parameter value is obtained by updating the first angle parameter value according to the local motion information of the prediction node, the second angle parameter value has the prior information of local motion compared to the first angle parameter value, thereby achieving a more refined prediction of the geometric information of the prediction node, thereby improving the accuracy of inter-frame prediction. In addition, since the second angle parameter value has the prior information of local motion, when the second angle parameter value of the prediction node is used to determine the reconstructed geometric information of the node to be decoded, the accuracy of the geometric reconstruction of the node to be decoded can be improved, thereby improving the decoding efficiency and accuracy of the geometric information of the point cloud.

In some embodiments of the present application, S1042 includes S201 to S202:

S201. Determine the rotation angular velocity of the laser radar corresponding to the node to be decoded.

In an embodiment of the present application, the angular velocity of rotation of the laser radar is the angular velocity of rotation of the laser radar corresponding to the current frame; or, the angular velocity of rotation of the laser radar is the angular velocity of rotation of the laser radar corresponding to the first reference frame; or, the angular velocity of rotation of the laser radar is the angular velocity of rotation of the laser radar corresponding to the second reference frame.

In the embodiment of the present application, the current frame, the first reference frame and the second reference frame may correspond to the same rotation angular velocity.

In the embodiment of the present application, the rotational angular velocity of the laser radar is related to the number of points (nodes) obtained by rotating the laser radar one circle. For example, the rotational angular velocity of the laser radar can be 2π/pointnums, where pointnums represents the number of points obtained by rotating the laser radar one circle.

In the embodiment of the present application, the rotational angular velocity of the laser radar can be a value specified or agreed upon by both the decoder and the encoder. In this case, the decoder can directly determine the rotational angular velocity of the laser radar.

In the embodiment of the present application, the rotation angular velocity of the laser radar can be directly obtained by parsing the code stream. The rotation angular velocity of the laser radar is encoded and the obtained coded bits are written into the bit stream. The decoder decodes the rotation angular velocity of the laser radar by parsing the bit stream to obtain the rotation angular velocity.

In an embodiment of the present application, the rotational angular velocity of the laser radar can also be determined based on the number of laser radar points obtained by parsing the code stream. The encoder encodes the number of laser radar points and writes the obtained coded bits into the code stream. The decoder decodes the number of laser radar points by parsing the code stream to obtain the number of laser radar points. Subsequently, the decoder determines the rotational angular velocity of the laser radar (2π/pointnums) based on the number of laser radar points.

In the embodiment of the present application, the rotational angular velocity of the laser radar can be a value specified or agreed upon by both the decoder and the encoder. In this case, the decoder can directly determine the rotational angular velocity of the laser radar.

S202: Determine a second angle parameter value based on the local motion information, the third angle parameter value and the rotation angular velocity.

In an embodiment of the present application, when the predicted node index value represents that the predicted node is a preset node, the decoder determines the second angle parameter value of the predicted node through the local motion information of the predicted node, the third angle parameter value of the first decoded node and the rotation angular velocity of the lidar.

In some embodiments of the present application, S202 includes S2021 to S2024:

S2021. Determine a first intermediate value based on the ratio of the local motion information to the rotation angular velocity.

In the embodiment of the present application, the decoder determines the first intermediate value according to the ratio of the local motion information of the prediction node to the rotation angular velocity of the laser radar, wherein the above process can be expressed as: in, It represents the local motion information of the prediction node, and angular azimuth speed represents the angular velocity of the lidar.

S2022. Perform a rounding operation on the first intermediate value to obtain a second intermediate value.

In the embodiment of the present application, after determining the first intermediate value, the decoder performs a rounding operation on the first intermediate value to obtain a second intermediate value. That is, the second intermediate value is a positive integer, and qphi0 is used to represent the second intermediate value.

S2023. Multiply the second intermediate value by the rotation angular velocity to obtain a third intermediate value.

In an embodiment of the present application, after determining the second intermediate value, the decoder multiplies the second intermediate value by the angular velocity of rotation to obtain a third intermediate value; wherein, the above process can be expressed as: qphi0*_geomAngularAzimuthSpeed; wherein, qphi0 represents the second intermediate value, and _geomAngularAzimuthSpeed represents the angular velocity of rotation of the lidar.

S2024. Add the third intermediate value and the third angle parameter value to obtain a second angle parameter value.

In the embodiment of the present application, after obtaining the third intermediate value, the decoder adds the third intermediate value to the third angle parameter value of the first decoded node to obtain the second angle parameter value of the predicted node; wherein the above process can be expressed as:

interPred.second[1]=prevPos[1]+qphi0*_geomAngularAzimuthSpeed;

Among them, prevPos[1] represents the third angle parameter value of the first decoded node, and interPred.second[1] represents the second angle parameter value of the predicted node.

In some embodiments of the present application, if the local motion information is greater than or equal to a first preset threshold, or the local motion information is less than or equal to a second preset threshold, the second angle parameter value of the prediction node is determined based on the local motion information; the first preset threshold is greater than the second preset threshold.

In some embodiments of the present application, if the local motion information is less than a first preset threshold and the local motion information is greater than a second preset threshold, the first angle parameter value is determined as the second angle parameter value; the first preset threshold is greater than the second preset threshold.

In the embodiment of the present application, when the local motion information of the prediction node is greater than or equal to the first preset threshold, or the local motion information is less than or equal to the second preset threshold, the decoder determines the second angle parameter value of the prediction node based on the local motion information of the prediction node; when the local motion information of the prediction node is less than the first preset threshold and the local motion information is greater than the second preset threshold, the decoder uses the first angle parameter value of the prediction node as the second angle parameter value. The above process can be expressed as:
if(deltaPhi>=(_geomAngularAzimuthSpeed>>1)||deltaPhi<=-(_geomAngularAzimuthSpeed>>
1));

Among them, _geomAngularAzimuthSpeed>>1 means shifting right by one bit, that is, _geomAngularAzimuthSpeed multiplied by 0.5.

In the embodiment of the present application, the first preset threshold and the second preset value are pre-set, and the first preset threshold is greater than the second preset threshold.

In some embodiments of the present application, the first preset threshold is Q times the rotation angular velocity, where Q is a positive number; and the second preset threshold is negative Q times the rotation angular velocity.

In the embodiment of the present application, Q is preset.

In the embodiment of the present application, Q is 0.5.

Exemplarily, the preset nodes are nodes e, f, o, and p in the first reference frame. When the predicted node index value indicates that the predicted node is a preset node, the decoder performs local motion processing on the first angle parameter value of the predicted node to obtain the second angle parameter value of the predicted node. That is, the predicted node (one of the nodes e, f, o, and p) is The first angle parameter value Replace it with the following local motion:

1) Subtract the fourth angle parameter value of the second decoded node (node g) from the first angle prediction value of the prediction node to obtain the local motion information of the prediction node, that is, the difference between the fourth angle parameter value and the first angle parameter value.

2) If the local motion information of the predicted node Greater than or equal to the first preset threshold (k times the rotation angle value angular azimuth speed), or, predict the local motion information of the node is less than or equal to a second preset threshold (minus k times the rotation angle value angular azimuth speed), proceed to step 3);

The k times here are the Q times mentioned above, and the two have the same meaning.

If the local motion information of the predicted node The local motion information of the predicted node is smaller than the first preset threshold (k times the rotation angle value angular azimuth speed) If it is greater than a second preset threshold (minus k times the rotation angle value angular azimuth speed), proceed to step 5);

3) Based on the ratio of the local motion information to the rotation angular velocity, determine the first intermediate value; perform rounding operation on the first intermediate value to obtain the second intermediate value. That is, calculate It should be noted that qphi0 represents the second intermediate value. It means rounding up, that is, qphi0 is an integer.

4) Multiply the second intermediate value by the rotational angular speed (angular azimuth speed) to obtain a third intermediate value, and add the third intermediate value to the third angle parameter value to obtain a second angle parameter value. That is, replace the first angle parameter value of the predicted node with the third angle parameter value of the first decoded node (a) plus the third intermediate value (qphi0*angular azimuth speed);

5) No local motion processing is performed on the first angle parameter value of the prediction node, and the first angle parameter value is directly determined as the second angle parameter value.

In the embodiment of the present application, the above steps can be expressed as:
auto deltaPhi = interPred.second[1] - interPredPrev.second[1]; // Determine the difference between the fourth angle parameter value and the first angle parameter value
if(
deltaPhi>=(_geomAngularAzimuthSpeed>>1)
||deltaPhi<＝-(_geomAngularAzimuthSpeed>>1)){//If this condition is met, the subsequent steps will be executed
int qphi0＝divApprox(
int64_t(deltaPhi)+(_geomAngularAzimuthSpeed>>1),
_geomAngularAzimuthSpeed,0); //Determine the second intermediate value
interPred.second[1]＝
prevPos[1]+qphi0*_geomAngularAzimuthSpeed; //Add the third intermediate value to the third angle parameter value to get the second angle parameter value
}

It can be understood that in the process of determining the prediction node, the decoder calculates the local motion information of the motion between the first angle parameter value of the prediction node (such as e) and the third angle parameter value of the first decoded node (such as a). By using this prior local motion information, better inter-frame prediction can be performed on the node to be decoded, thereby achieving a more refined prediction of the geometric information of the prediction node, thereby improving the accuracy of inter-frame prediction.

In some embodiments of the present application, S103 includes S1031 to S1032:

S1031. According to the first decoded node, determine a second decoded node in a reference frame where the predicted node represented by the predicted node index value is located; the fourth angle parameter value of the second decoded node is less than or equal to and closest to the third angle parameter value of the first decoded node, and the second decoded node has the same radar index as the first decoded node.

In an embodiment of the present application, a second decoded node is determined in a reference frame where the prediction node is located according to the third angle parameter value of the first decoded node.

In the embodiment of the present application, the second decoded node is determined according to the third angle parameter value.

In an embodiment of the present application, the reference frame where the second decoded node is located has the same radar index as the current frame. Therefore, the second decoded node has the same radar index as the first decoded node, that is, it corresponds to the same laser radar.

Exemplarily, based on FIG. 23 , in the first reference frame, the second decoded node is node g, and in the second reference frame, the second decoded node is node b.

Wherein, node g is a decoded node in the first reference frame that has the same radar index as the first decoded node (a) and whose first angle parameter value is less than or equal to the third angle parameter value of the first decoded node. Node b is a decoded node in the second reference frame that has the same radar index as the first decoded node (a) and whose first angle parameter value is less than or equal to the third angle parameter value of the first decoded node.

In the embodiment of the present application, the predicted node index value includes at least one node index value corresponding to at least one reference frame. That is, the predicted node index value corresponds to which reference frame the node index value belongs to. That is, the predicted node index value can be used to know the predicted node index value. The reference frame where the measured node is located.

In an embodiment of the present application, the determination order corresponding to the prediction node can be determined according to the prediction node index value of the prediction node. Exemplarily, based on Figure 23, when the prediction node index value of the prediction node (node e) is 2, the determination order of the prediction node is ge, that is, first determine node g, and then determine node e based on node g. For another example, when the prediction node index value of the prediction node (node f) is 3, the determination order of the prediction node is gef, that is, first determine node g, then determine node e based on node g, and finally determine node f based on node e.

Exemplarily, when the prediction node index value is 0 (corresponding to node c), it can be known that the reference frame where the prediction node represented by the prediction node index value 0 is located is the second reference frame; when the prediction node index value is 2 (corresponding to node e), it can be known that the reference frame where the prediction node represented by the prediction node index value 2 is located is the first reference frame.

S1032. Determine a predicted node based on the second decoded node, wherein a first angle parameter value of the predicted node is greater than a fourth angle parameter value of the second decoded node, and the predicted node and the second decoded node have the same radar index.

In the embodiment of the present application, a predicted node is determined in a reference frame where the second decoded node is located according to the fourth angle parameter value of the second decoded node.

In the embodiment of the present application, the predicted node is determined according to the fourth angle parameter value of the second decoded node.

Exemplarily, when the second decoded node is node g, the predicted node is determined in the first reference frame according to the angle parameter value of node g. When the second decoded node is node b, the predicted node is determined in the second reference frame according to the angle parameter value of node b.

In the embodiment of the present application, since the predicted node and the second decoded node belong to the same reference frame, the predicted node and the second decoded node have the same radar index.

In some embodiments of the present application, S1032 includes S10321 to S10322:

S10321. Use the fourth angle parameter value corresponding to the second decoded node as the first angle parameter value of the predicted node.

In an embodiment of the present application, when the predicted node index value indicates that the predicted node is the second decoded node, the second decoded node is used as the predicted node, and the fourth angle parameter value of the second decoded node is used as the first angle parameter value of the predicted node.

Exemplarily, based on FIG. 23 , assuming that the index value of the prediction node is 9 (corresponding to node g), and the second decoded node in the first reference frame is node g, node g is used as the prediction node. Assuming that the index value of the prediction node is 8 (corresponding to node b), and the second decoded node in the second reference frame is node b, node b is used as the prediction node.

S10322. In the reference frame where the predicted node is located, based on the second decoded node and the predicted node index value, determine at least one next decoded node, wherein the at least one next decoded node includes the predicted node; a next angle parameter value of the next decoded node is greater than and closest to a previous angle parameter value of its previous decoded node, and at least one next decoded node has the same radar index as the second decoded node.

In an embodiment of the present application, in a reference frame where the predicted node is located, the next decoded node can be determined according to the predicted node index value and the second decoded node; and the next decoded node of the next decoded node can be determined according to the next decoded node to obtain at least one next decoded node. The at least one next decoded node includes the predicted node, and the radar indexes of the at least one next decoded node are the same.

In an embodiment of the present application, when the predicted node index value indicates that the predicted node is not the second decoded node, in the reference frame where the predicted node is located, at least one next decoded node is determined based on the second decoded node and the predicted node index value.

In an embodiment of the present application, based on the second decoded node, a preset number of at least one next decoded node is determined in the reference frame where the prediction node is located; at this time, the prediction node is one of the at least one next decoded nodes; or, based on the second decoded node, the next decoded node is determined in the reference frame where the prediction node is located, until the prediction node corresponding to the prediction node index value is determined, at this time, the last decoded node is the prediction node, and the present application does not limit this.

Exemplarily, the predicted node index value is 2. The next decoded node can be determined based on the second decoded node, and two decoded nodes are obtained. The predicted node is the next decoded node. The next decoded node can also be determined based on the second decoded node; the next decoded node of the next decoded node is determined based on the next decoded node, and three decoded nodes are obtained. The predicted node is the next decoded node.

Exemplarily, based on FIG. 23 , assuming that the preset number is 4 and the predicted node index value is 6 (corresponding to node o), at this time, it is necessary to determine 4 next decoded nodes in the reference frame where the predicted node is located: the first decoded node (node e), the second decoded node (node f), the third decoded node (node o) and the fourth decoded node (node p). Then, in the first reference frame where the predicted node is located, based on the second decoded node (node g), the first decoded node (node e), the second decoded node (node f), the third decoded node (node o) and the fourth decoded node (node p) are determined in sequence, for a total of 4 next decoded nodes. According to the predicted node index value (6), among the obtained 4 next decoded nodes, the third decoded node (node o) corresponding to the predicted node index value is determined, and the third decoded node (node o) is used as the predicted node.

In an embodiment of the present application, when the predicted node index value indicates that the predicted node is not the second decoded node, in the reference frame where the predicted node is located, the next decoded node is determined based on the second decoded node until the predicted node is determined.

In the embodiment of the present application, the predicted node and the second decoded node correspond to the same reference frame.

In an embodiment of the present application, when the predicted node index value indicates that the predicted node is not the second decoded node, the i-th decoded node is determined in the reference frame where the predicted node is located based on the second decoded node; wherein i is a positive integer greater than or equal to 1 and less than M; the i-th angle parameter value of the i-th decoded node is greater than the fourth angle parameter value; when the i-th decoded node is not the predicted node, continue to determine the i+1-th decoded node based on the i-th decoded node until the i+1-th decoded node is the predicted node; wherein, the i+1-th angle parameter value of the i+1-th decoded node is greater than the i-th angle parameter value of the i-th decoded node.

In the embodiment of the present application, the i+1th decoded node is a predicted node, and the i+1th decoded node is the last decoded node.

Example 1: Based on Figure 23, the second decoded node in the first reference frame (the reference frame after the second reference frame undergoes global motion) is node g, and the first reference frame includes, in addition to the second decoded node: the first decoded node (node e), the second decoded node (node f), the third decoded node (node o) and the fourth decoded node (node p). When the predicted node index value of the predicted node indicates that the predicted node is the second decoded node (node f), that is, i=2, and, according to the predicted node index value, the determination order of the predicted node can be determined as gef, then the predicted node can be determined by the following steps:

1) Based on the second decoded node (node g), determine the first decoded node (node e) in the first reference frame where the prediction node is located, wherein the first angle parameter value of the first decoded node (node e) is greater than the fourth angle parameter value of the second decoded node (node g);

2) Based on the first decoded node (node e), determine the second decoded node (node f) in the first reference frame where the prediction node is located, wherein the second angle parameter value of the second decoded node (node f) is greater than the first angle parameter value of the first decoded node (node e).

Example 2: Based on FIG. 23 and Example 1, when the predicted node index value of the predicted node indicates that the predicted node is the fourth decoded node (node p), that is, i=4, and the determination order of the predicted node can be determined as gefop according to the predicted node index value, the predicted node can be determined by the following steps:

1) Based on the second decoded node (node g), determine the first decoded node (node e) in the first reference frame where the prediction node is located, wherein the first angle parameter value of the first decoded node (node e) is greater than the fourth angle parameter value of the second decoded node (node g);

2) Based on the first decoded node (node e), determine the second decoded node (node f) in the first reference frame where the prediction node is located, wherein the second angle parameter value of the second decoded node (node f) is greater than the first angle parameter value of the first decoded node (node e);

3) Based on the second decoded node (node f), determine the third decoded node (node o) in the first reference frame where the prediction node is located, wherein the third angle parameter value of the third decoded node (node o) is greater than the second angle parameter value of the second decoded node (node f);

4) Based on the third decoded node (node o), determine the fourth decoded node (node p) in the first reference frame where the prediction node is located, wherein the fourth angle parameter value of the fourth decoded node (node p) is greater than the third angle parameter value of the third decoded node (node o).

Example 3: Based on Figure 23, the second decoded node in the second reference frame (the first decoded frame before the current frame) is node b, and the second reference frame includes, in addition to the second decoded node: the first decoded node (node c), the second decoded node (node d), the third decoded node (node m) and the fourth decoded node (node n). When the predicted node index value of the predicted node indicates that the predicted node is the fourth decoded node (node n), that is, i=4, and the determination order of the predicted node can be determined as bcdmn according to the predicted node index value, the predicted node can be determined by the following steps:

1) Based on the second decoded node (node b), determine the first decoded node (node c) in the second reference frame where the prediction node is located, wherein the first angle parameter value of the first decoded node (node c) is greater than the fourth angle parameter value of the second decoded node (node b);

2) Based on the first decoded node (node c), determine the second decoded node (node d) in the second reference frame where the prediction node is located, wherein the second angle parameter value of the second decoded node (node d) is greater than the first angle parameter value of the first decoded node (node c);

3) Based on the second decoded node (node d), determine the third decoded node (node m) in the second reference frame where the prediction node is located, wherein the third angle parameter value of the third decoded node (node m) is greater than the second angle parameter value of the second decoded node (node d);

4) Based on the third decoded node (node m), determine the fourth decoded node (node n) in the second reference frame where the prediction node is located, wherein the fourth angle parameter value of the fourth decoded node (node n) is greater than the third angle parameter value of the third decoded node (node m).

Example 4. Based on Figure 23 and Example 1, if the predicted node index value represents that the predicted node is the second decoded node (node g), then node g in the first reference frame where the predicted node is located is used as the predicted node, where the fourth angle parameter value of the second decoded node (node g) is less than or equal to the third angle parameter value of the first decoded node (node a).

Example 5. Based on Example 3, if the predicted node index value represents that the predicted node is the second decoded node (node b), then node b in the second reference frame where the predicted node is located is used as the predicted node, wherein the fourth angle parameter value of the second decoded node (node b) is less than or equal to the third angle parameter value of the first decoded node (node a).

In some embodiments of the present application, S103 includes S301 to S303:

S301. According to the first decoded node, in a reference frame where the predicted node represented by the predicted node index value is located, determine a second decoded node; a fourth angle parameter value of the second decoded node is less than or equal to and closest to a third angle parameter value of the first decoded node, and the second decoded node and the first decoded node have the same radar index.

In an embodiment of the present application, based on the first angle parameter of the first decoded node, in the reference frame where the predicted node represented by the predicted node index value is located, the decoded node corresponding to the third angle parameter value that is less than or equal to and closest to the first decoded node is determined as the second decoded node.

S302: Use the fourth angle parameter value corresponding to the second decoded node as the first angle parameter value of the predicted node.

In an embodiment of the present application, when the predicted node represented by the predicted node index value is the second decoded node, the second decoded node is used as the predicted node, that is, the second angle parameter of the second decoded node is used as the first angle parameter value of the predicted node.

S303 . Determine a prediction node among the decoded nodes after the second decoded node according to the order of the prediction tree.

In the embodiment of the present application, when the prediction node represented by the prediction node index value is not the second decoded node, the prediction node is determined according to the order of the prediction tree.

In the embodiment of the present application, a prediction tree method is used to determine the prediction node.

In an embodiment of the present application, when the predicted node represented by the predicted node index value is not the second decoded node, and the fourth angle parameter value of the second decoded node is equal to the third angle parameter value of the first decoded node, and the second decoded node and the first decoded node have the same radar index, the predicted node is determined according to the order of the prediction tree.

It should be noted that, in an embodiment of the present application, determining the previous decoded node of the current node may include: determining a prediction tree corresponding to the current frame; and determining the previous decoded node of the current node based on the decoding order of the prediction tree.

In the embodiment of the present application, it is first necessary to construct a prediction tree corresponding to the current frame. Among them, the prediction tree structure can be constructed in two different ways, which can include: KD-Tree (high-latency slow mode) and low-latency fast mode (using laser radar calibration information). When using laser radar calibration information, each point is divided into different lasers, and the prediction tree structure is established according to different lasers.

It should also be noted that, in the embodiment of the present application, the decoding order of the prediction tree can be one of the following: unordered, Morton order, azimuth order, radial distance order, etc., which is not specifically limited here.

Thus, at the decoding end, the prediction tree structure is reconstructed by parsing the bitstream, and then the prediction tree is traversed to determine the previous point of the node to be decoded in the decoding order of the prediction tree, which is the previous decoded node of the node to be decoded (i.e., the first decoded node).

Exemplarily, it is assumed that the decoded nodes after the second decoded node (node b) in the second reference frame include: node c, node d, node m and node n. When the predicted node is characterized as node d according to the predicted node index value of the predicted node, the previous decoded node a of the node to be decoded is first determined; then the second decoded node b is determined in the second reference frame based on the angle parameter value of the decoded node a; according to the decoding order of the prediction tree, the nodes c and d after the second decoded node b are determined in the second reference frame in sequence; at this time, the last node d determined is the predicted node.

In some embodiments of the present application, the depth information of the predicted node, the radar index value of the predicted node, and the second angle parameter value are determined as the geometric prediction value of the node to be decoded.

In an embodiment of the present application, after the prediction node is determined, the geometric parameters (such as geometric position information) may be used as the geometric prediction value of the node to be decoded.

In the embodiment of the present application, the geometric parameters here refer to the parameters in the radar coordinate system. Among them, the geometric parameters may include: horizontal azimuth Radar laser index value laserID and the depth information radius of the predicted node.

In the embodiment of the present application, the second angle parameter value is the first angle parameter value of the prediction node or the angle prediction value after local motion processing is performed on the first angle parameter value.

In some embodiments of the present application, the method further includes: parsing the bitstream to determine the geometric residual information and quantization parameters of the point to be decoded; performing inverse quantization processing on the geometric residual information based on the quantization parameters to determine the geometric prediction residual; The predicted value is used to determine the reconstructed geometric parameters of the point to be decoded.

In an embodiment of the present application, determining the reconstructed geometric parameters of the node to be decoded based on the geometric prediction residual and the geometric prediction value may include: performing an addition operation based on the geometric prediction residual and the geometric prediction value to determine the reconstructed geometric parameters of the node to be decoded.

In an embodiment of the present application, the geometric residual information of the node to be decoded is obtained by parsing the bit stream, and the quantization parameter is obtained by decoding the bit stream; then, the geometric residual information is inversely quantized according to the quantization parameter to obtain the geometric prediction residual; then, the geometric prediction residual and the geometric prediction value are summed to obtain the reconstructed geometric parameters of the node to be decoded, such as restoring the reconstructed geometric position information of the node to be decoded, and finally completing the geometric reconstruction at the decoding end.

In some embodiments of the present application, determining geometric residual information of a point to be decoded includes:

Determine the context model of the node to be decoded according to the predicted node index value;

The context model is used to decode the geometric residual information of the node to be decoded to obtain the geometric residual information.

In an embodiment of the present application, a context model corresponding to a node to be decoded is determined according to a predicted node index value, and the decoder uses the context model corresponding to the node to be decoded to decode the geometric residual information of the node to be decoded, thereby obtaining the geometric residual information.

That is to say, different decoded nodes in the reference frame may correspond to different context models. Alternatively, decoded nodes in different reference frames may correspond to different context models. Alternatively, at least one decoded node in different reference frames may correspond to different context models, which is not limited in the present application.

Exemplarily, for selecting the inter-frame prediction mode as node c or node d or node m or node n or node b, a parameter for selecting a context model corresponds to a parameter for selecting a context model, and for selecting the inter-frame prediction mode as node e or node f or node o or node p or node g, another parameter for selecting a context model corresponds to perform entropy decoding of the subsequent geometric residual information.

Further, in the embodiments of the present application, the decoding method is mainly for decoding optimization of the inter-frame prediction mode, and a flag bit can be used to determine whether the current node uses the inter-frame prediction mode. Therefore, in some embodiments of the present application, the method further includes:

Parse the bitstream to determine the first identification information; when the first identification information indicates that the node to be decoded uses the inter-frame prediction mode, perform the step of determining the prediction node according to the node index value and the first decoded node.

Further, for the first identification information, in some embodiments of the present application, the method further includes:

If the first identification information is the first value, determining that the first identification information indicates that the node to be decoded does not use the inter-frame prediction mode;

If the first identification information is the second value, it is determined that the first identification information indicates that the node to be decoded uses the inter-frame prediction mode.

It should be noted that in the embodiment of the present application, the first value is different from the second value, and the first value and the second value can be in parameter form or in digital form. Specifically, the first identification information can be a parameter written in the profile or a flag value, which is not specifically limited here.

Exemplarily, for the first value and the second value, the first value can be set to 1 and the second value can be set to 0; or, the first value can be set to 0 and the second value can be set to 1; or, the first value can be set to true and the second value can be set to false; or, the first value can be set to false and the second value can be set to true; but this is not specifically limited here.

In an embodiment of the present application, taking the flag written into the bitstream as an example, assuming that the first value is set to 0 (false) and the second value is set to 1 (true), if the value of the first identification information is 0 (false), then it can be determined that the inter-frame prediction mode is not used for the node to be decoded, that is, there is no need to execute the decoding method described in the embodiment of the present application; if the value of the first identification information is 1 (true), then it can be determined that the inter-frame prediction mode is used for the node to be decoded, that is, the decoding method described in the embodiment of the present application needs to be executed.

It should be noted that the embodiments of the present application do not limit the expression forms of the first value and the second value.

Further, in the embodiment of the present application, a flag bit can be set here to determine whether to enable the decoding method of the embodiment of the present application. Therefore, in some embodiments of the present application, the method further includes: parsing the code stream to determine the second identification information; when the second identification information indicates that the node to be decoded enables the local motion processing mode, performing the step of performing local motion processing on the first angle parameter value of the predicted node based on the first decoded node to determine the second angle parameter value of the predicted node.

Further, for the second identification information, in some embodiments of the present application, the method further includes:

If the second identification information is the first value, determining that the second identification information indicates that the node to be decoded does not enable the local motion processing mode;

If the second identification information is the second value, it is determined that the second identification information indicates that the node to be decoded enables a local motion processing mode.

It should be noted that in the embodiment of the present application, the first value is different from the second value, and the first value and the second value can be in parameter form or in digital form. Specifically, the second identification information can be a parameter written in the profile or a flag value, which is not specifically limited here.

In the embodiment of the present application, taking the flag written into the bitstream as an example, assuming that the first value is set to 0 (false) and the second value is set to 1 (true), if the value of the second identification information is 0 (false), then it can be determined that local motion processing is not enabled for the node to be decoded, that is, there is no need to execute the decoding method described in the embodiment of the present application; if the value of the second identification information is 1 (true), then it can be determined that local motion processing is enabled for the node to be decoded, that is, the decoding method described in the embodiment of the present application needs to be executed.

In short, in the embodiment of the present application, a 1-bit flag (i.e., the second identification information) can be used here to indicate whether the decoding method of the embodiment of the present application is enabled or not. This flag can be placed in the header information of the high-level syntax element, such as the geometry header; and this flag can be conditionally enabled under certain conditions. If this flag does not appear in the bitstream, its default value is a fixed value. At the decoding end, if this flag does not appear in the bitstream, decoding may not be performed, and its default value is a fixed value.

This embodiment provides a decoding method, which includes: the decoder first parses the code stream to determine the predicted node index value corresponding to the node to be decoded; then, the decoder determines the first decoded node before the node to be decoded in the current frame; then, the decoder determines the predicted node based on the predicted node index value and the first decoded node; then, the decoder performs local motion processing on the first angle parameter value of the predicted node based on the first decoded node to determine the second angle parameter value of the predicted node; finally, the decoder determines the geometric prediction value of the node to be decoded based on the first angle parameter value or the second angle parameter value of the predicted node. Since the decoder performs local motion processing on the first angle parameter value of the predicted node to obtain the second angle parameter value, the second angle parameter value has prior information related to the local motion, so that the inter-frame prediction can better predict the node to be decoded, which can improve the accuracy of the inter-frame prediction, thereby improving the decoding efficiency of the geometric information of the point cloud and improving the decoding performance of the point cloud.

In another embodiment of the present application, referring to FIG22, a schematic diagram of a flow chart of an encoding method provided in an embodiment of the present application is shown. As shown in FIG22, the method may include:

S401 , determining a first encoded node preceding a node to be encoded in a current frame.

In the embodiment of the present application, the first encoded node corresponds to the first decoded node of the decoding end.

In some embodiments of the present application, determining a first encoded node preceding a node to be encoded in a current frame may include:

Based on the coding order of the prediction tree, a previous coded node of the node to be coded is determined, and the previous coded node is used as the first coded node.

In the embodiment of the present application, according to the coding order of the prediction tree corresponding to the current frame, the previous coded node of the node to be coded is used as the first coded node.

Exemplarily, at the encoding end, the first encoded node is node a; correspondingly, at the decoding end, the first decoded node is node a.

It should be noted that the first angle parameter of the first encoded node at the encoding end corresponds to the first angle parameter of the first decoded node at the decoding end.

In the embodiment of the present application, the node to be encoded is one of the points in the current frame.

It should be noted that the encoding method of the embodiment of the present application is applied to an encoder. In addition, the encoding method may specifically refer to a point cloud inter-frame prediction method; or it may be a method for encoding geometric information between point cloud frames, which mainly improves the inter-frame prediction algorithm in the relevant technology, and can perform local motion processing on the angle parameter value of the prediction node, thereby achieving a better inter-frame prediction effect.

In an embodiment of the present application, the current frame is a frame where the current node to be encoded is located, and the current frame includes at least one point.

In an embodiment of the present application, the current frame is obtained by scanning a circle of the laser radar along the XY plane (horizontal plane), and the current frame may include multiple points.

In the embodiments of the present application, the node to be encoded is also referred to as a point to be encoded, a current node, a current point, a current node to be encoded, a current point to be encoded, etc., and the present application does not limit this.

In an embodiment of the present application, the node to be encoded may be a point in the current point cloud to be encoded, or the node to be encoded may include multiple points in the current point cloud to be encoded, which is not limited in the present application.

It should be noted that, when the node to be encoded includes multiple points in the current point cloud to be encoded, the multiple points included in the node to be encoded are repeated points. In this case, the node to be encoded includes multiple points having the same geometric prediction information.

In the embodiment of the present application, when the first encoded node before the node to be encoded in the current frame is determined, the geometric information (geometric position information) of the first encoded node is determined.

It should be noted that the first encoded node here refers to the geometric information of the first encoded node. That is to say, after determining the first encoded node before the node to be encoded in the current frame, the geometric information of the first encoded node in the point cloud is determined. The geometric information here can be understood as the position information of the first encoded node in the point cloud. For example, the geometric information of the first encoded node can be radar coordinate information or Cartesian coordinate information, etc., and this application does not make any limitation on this.

It should also be noted that in the embodiment of the present application, the geometric parameters (geometric information) here refer to the parameters in the radar coordinate system. Among them, the geometric parameters may include: horizontal azimuth Radar laser index value laserID and depth information radius.

In an embodiment of the present application, when the geometric information of the first encoded node is radar coordinate information, the geometric information of the first encoded node at least includes an angle parameter corresponding to the first encoded node, that is, a third angle parameter value.

In the embodiment of the present application, the third angle parameter value of the first encoded node is the angle information of the horizontal position of the first encoded node on the horizontal plane.

In the embodiment of the present application, the first encoded node is the previous encoded node of the node to be encoded in the current frame.

It should be noted that, since the first encoded node is the previously encoded node of the node to be encoded, the first angle parameter of the first encoded node is smaller than the angle parameter of the node to be encoded.

It should be noted that, in the embodiment of the present application, the first encoded node may also be any H encoded nodes before the node to be encoded in the current frame, where H is a positive integer greater than or equal to 1. For example, the first encoded node may be the two encoded nodes before the node to be encoded in the current frame, the first encoded node may also be the four encoded nodes before the node to be encoded in the current frame, etc., and the present application does not limit this.

S402, determining a first candidate node having at least one geometric parameter identical to that of a first encoded node in a reference frame, and determining at least one second candidate node in the reference frame based on the first candidate node.

In the embodiment of the present application, the first candidate node corresponds to the second decoded node at the decoding end.

Exemplarily, at the encoding end, based on Figure 23, the first candidate node in the first reference frame is node g, and the first candidate node in the second reference frame is node b; correspondingly, at the decoding end, the second decoded node in the first reference frame is node g, and the second decoded node in the second reference frame is node b.

In the embodiment of the present application, the second candidate node corresponds to a decoded node other than the second decoded node in the reference frame where the second decoded node of the decoding end is located.

Exemplarily, at the encoding end, based on Figure 23, the second candidate nodes in the first reference frame are node e, node f, node o and node p, and the second candidate nodes in the second reference frame are node c, node d, node m and node n; correspondingly, at the decoding end, the decoded nodes in the first reference frame except the second decoded node (node g) are node e, node f, node o and node p, and the decoded nodes in the second reference frame except the second decoded node (node b) are node c, node d, node m and node n.

In the embodiment of the present application, the geometric parameters (geometric information) here refer to the parameters in the radar coordinate system. Among them, the geometric parameters may include: horizontal azimuth Radar laser index value laserID and depth information radius.

In the embodiment of the present application, the angle parameter value is the angle information of the horizontal position of the horizontal plane, that is,

In the embodiment of the present application, the fourth angle parameter value of the first candidate node is less than or equal to and closest to the third angle parameter value of the first encoded node. The reference frame includes: a first reference frame and a second reference frame; the first reference frame is at least one frame obtained by global motion of the second reference frame; the second reference frame is an encoded frame of the previous K frames of the current frame, where K is an integer greater than 0. The preset node is at least one candidate node in the first reference frame except the first candidate node.

In an embodiment of the present application, at least one second candidate node, the first candidate node, and the first encoded node have the same radar index.

In some embodiments of the present application, the fourth angle parameter value of the first candidate node is less than or equal to and closest to the third angle parameter value of the first encoded node.

In an embodiment of the present application, the first candidate node and the first encoded node may have the same radar index, or the first candidate node and the first encoded node may have different radar indexes; the first candidate node and the first encoded node may have the same depth information, or the first candidate node and the first encoded node may have different depth information; the first candidate node and the first encoded node may have the same angle parameter value, or the first candidate node and the first encoded node may have different angle parameter values, which is not limited in the present application.

In some embodiments of the present application, the reference frame includes: a first reference frame and a second reference frame; the first reference frame is at least one frame obtained by performing global motion on the second reference frame; the second reference frame is an encoded frame of the previous K frames of the current frame, where K is an integer greater than 0.

In an embodiment of the present application, the second reference frame may be a frame before the current frame; the first reference frame may be a frame before the frame before the current frame. For example, if the current frame is Frame t, the first reference frame may be Frame t-1, and the second reference frame may be Frame t-2; t is an integer.

It should also be noted that, in the embodiment of the present application, a third reference frame may also be included, and the number of reference frames and the number of candidate nodes are not specifically limited. In the embodiment of the present application, only the first reference frame and the second reference frame are used as examples for detailed description.

It should be noted that the preset node in the decoding end is at least one candidate node other than the first candidate node in the first reference frame of the encoding end, that is, the preset node is at least one candidate node in at least one second candidate node.

S403: Perform local motion processing on the angle parameter value of at least one candidate node among the at least one second candidate node to obtain at least one updated second candidate node.

In an embodiment of the present application, local motion processing is performed on the angle parameter value of at least one candidate node among at least one second candidate node according to the fourth angle parameter value of the first candidate node to obtain at least one updated second candidate node.

In the embodiment of the present application, the fourth angle parameter value of the first candidate node corresponds to the fourth angle parameter value of the second decoded node at the decoding end. Parameter value.

It can be understood that since at least one of the at least one second candidate nodes is subjected to local motion processing to obtain at least one updated second candidate node, the updated at least one second candidate node has the prior information of local motion compared to the non-updated second candidate node, thereby achieving a more refined prediction of the geometric information of the predicted node, thereby improving the accuracy of inter-frame prediction.

It can be understood that, since at least one second candidate node takes into account the prior information of local motion, when the geometric prediction information of the node to be encoded is determined using at least one second candidate node, the accuracy of the prediction of the node to be encoded can be improved.

S404: Determine a geometric prediction value of the node to be encoded based on the first candidate node and at least one updated second candidate node.

In an embodiment of the present application, the geometric prediction value of the node to be encoded corresponds to the geometric prediction value of the prediction node at the decoding end.

In an embodiment of the present application, the geometric prediction value of the node to be encoded is determined based on the geometric information of the first candidate node (such as node g and/or node b) and at least one updated second candidate node (such as at least one of nodes c, d, m, n, e, f, o, p).

It can be understood that since the angle parameter value of at least one of the at least one second candidate node after update has been processed with local motion, at least one of the at least one second candidate node after update has the prior information of local motion, thereby more accurately determining the geometric prediction value of the node to be encoded.

In an embodiment of the present application, the encoder first determines the first encoded node preceding the node to be encoded in the current frame; then, the encoder determines a first candidate node having at least one geometric parameter identical to the first encoded node in the reference frame, and determines at least one second candidate node in the reference frame based on the first candidate node; then, the encoder performs local motion processing on the angle parameter value of at least one candidate node in the at least one second candidate node to obtain at least one updated second candidate node; finally, the encoder determines the geometric prediction value of the node to be encoded based on the first candidate node and the at least one updated second candidate node. Since the encoder performs local motion processing on the angle parameter value of at least one candidate node in the at least one second candidate node, at least one candidate node in the at least one second candidate node has prior information related to local motion, the accuracy of inter-frame prediction can be improved, thereby improving the coding efficiency of the geometric information of the point cloud and improving the coding performance of the point cloud.

In the embodiment of the present application, determining the first encoded node of the node to be encoded in the current frame may include:

Determine the prediction tree corresponding to the current frame;

Based on the coding order of the prediction tree, the first coded node of the node to be coded is determined.

It should be noted that in the embodiment of the present application, it is first necessary to construct a prediction tree corresponding to the current frame. Among them, the prediction tree structure can be constructed in two different ways, which can include: KD-Tree (high-latency slow mode) and low-latency fast mode (using laser radar calibration information). When using laser radar calibration information, each point is divided into different lasers, and the prediction tree structure is established according to different lasers.

It should also be noted that, in the embodiment of the present application, the encoding order of the prediction tree can be one of the following: unordered, Morton order, azimuth order, radial distance order, etc., which is not specifically limited here.

Thus, at the encoding end, a prediction tree structure is first constructed, and then the prediction tree is traversed to determine the point before the node to be encoded in the encoding order of the prediction tree, that is, the first encoded node (such as node a) of the node to be encoded.

In some embodiments of the present application, S403 includes S4031 to S4033:

S4031. Determine local motion information of each third candidate node based on the fourth angle parameter value of the first candidate node and the fifth angle parameter value of at least one third candidate node in at least one second candidate node that matches the preset node.

In the embodiment of the present application, the fourth angle parameter value of the first candidate node at the encoding end corresponds to the angle parameter value of the second decoded node at the decoding end.

In the embodiment of the present application, the second candidate node at the encoding end is a decoded node other than the second decoded node in the reference frame where the second decoded node at the decoding end is located.

In the embodiment of the present application, the preset nodes are candidate nodes specified or agreed upon by both the decoder and the encoder. In other words, the preset nodes are pre-specified candidate nodes for which local motion processing is performed.

Exemplarily, based on FIG. 23 , the decoder and the encoder agree to perform local motion processing on nodes e, f, o, and p in the first reference frame, that is, the preset nodes are nodes e, f, o, and p.

In the embodiment of the present application, the third candidate node is at least one candidate node among the preset nodes.

Exemplarily, the preset nodes are node e, node f, node o and node p, and the third candidate node is at least one of node e, node f, node o and node p.

In some embodiments of the present application, S4031 may include S501 to S502:

S501: Determine at least one third candidate node matching a preset node from at least one second candidate node.

Exemplarily, based on FIG. 23, at least one second candidate node may include: node e, node f, node o and node p, and node c, node d, node m and node n in the second reference frame. The preset nodes may be node e, node p, node c, node d. Then, the third candidate node may be at least one of node e, node p, node c, node d.

S502: Determine the difference between the fourth angle parameter value of the first candidate node and the fifth angle parameter value of each third candidate node as the local motion information of each third candidate node.

In the embodiment of the present application, the difference between the fourth angle parameter value and the fifth angle parameter value of each third candidate node may be used as the local motion information of each third candidate node.

In the embodiment of the present application, the difference between the fourth angle parameter value multiplied by the first weight and the fifth angle parameter value of each third candidate node multiplied by the second weight may be used as local motion information.

Exemplarily, the difference between the fourth angle parameter value and the fifth angle parameter value of each third candidate node is used as the local motion information, which can be expressed as:
auto deltaPhi=interPred.second[1]-interPredPrev.second[1];

Among them, deltaPhi represents the difference (difference value) between the fourth angle parameter value and the fifth angle parameter value of each third candidate node, interPred.second[1] represents the fifth angle parameter value of each third candidate node, and interPredPrev.second[1] represents the fourth angle parameter value of the first candidate node.

S4032. Based on the local motion information, update the fifth angle parameter value of the corresponding third candidate node, determine the updated fifth angle parameter value of at least one third candidate node, and thus determine the updated at least one third candidate node.

It can be understood that since the updated at least one third candidate node has the prior information of local motion compared to the at least one third candidate node that has not been updated, a more refined prediction of the geometric information of the node to be encoded can be achieved, thereby improving the accuracy of inter-frame prediction, thereby improving the encoding efficiency and accuracy of the geometric information of the point cloud.

S4033: Use the candidate nodes other than the at least one third candidate node among the at least one updated third candidate node and the at least one second candidate node as the at least one updated second candidate node.

In some embodiments of the present application, S4032 may include S601 to S602:

S601, determining the rotation angular velocity of the laser radar corresponding to the node to be encoded.

In an embodiment of the present application, the angular velocity of rotation of the laser radar is the angular velocity of rotation of the laser radar corresponding to the current frame; or, the angular velocity of rotation of the laser radar is the angular velocity of rotation of the laser radar corresponding to the first reference frame; or, the angular velocity of rotation of the laser radar is the angular velocity of rotation of the laser radar corresponding to the second reference frame.

In the embodiment of the present application, the rotational angular velocity of the laser radar is related to the number of points (nodes) obtained by rotating the laser radar one circle. For example, the rotational angular velocity of the laser radar can be 2π/pointnums, where pointnums represents the number of points obtained by rotating the laser radar one circle.

In the embodiment of the present application, the rotational angular velocity of the laser radar can be a value specified or agreed upon by both the decoder and the encoder. In this case, the encoder can directly determine the rotational angular velocity of the laser radar.

S602: Determine an updated fifth angle parameter value of at least one third candidate node based on the local motion information, the third angle parameter value, and the rotation angular velocity of each third candidate node.

In some embodiments of the present application, S602 may include S6021 to S6024:

S6021. Determine a first intermediate value of each third candidate node based on a ratio of the local motion information of each third candidate node to the rotation angular velocity.

In the embodiment of the present application, the encoder determines the first intermediate value of each third candidate node according to the ratio of the local motion information of each third candidate node to the rotation angular velocity of the laser radar, wherein the above process can be expressed as: in, Characterizes the local motion information of each third candidate node, and angular azimuth speed characterizes the rotation angular speed of the lidar.

S6022. Perform a rounding operation on the first intermediate value of each third candidate node to obtain a second intermediate value of each third candidate node.

In the embodiment of the present application, after determining the first intermediate value of each third candidate node, the encoder performs a rounding operation on the first intermediate value of each third candidate node to obtain the second intermediate value of each third candidate node. That is, the second intermediate value of each third candidate node is a positive integer, and qphi0 is used to represent the second intermediate value; the above process can be expressed as: It means rounding up, that is, qphi0 is an integer.

S6023. Multiply the second intermediate value of each third candidate node by the rotation angular velocity to obtain a third intermediate value of each third candidate node.

In an embodiment of the present application, after determining the second intermediate value of each third candidate node, the encoder multiplies the second intermediate value of each third candidate node by the rotation angular velocity to obtain the third intermediate value of each third candidate node; the above process can be expressed as: qphi0*_geomAngularAzimuthSpeed; wherein qphi0 represents the second intermediate value of each third candidate node, and _geomAngularAzimuthSpeed represents the rotation angular velocity of the lidar.

S6024. Add the third intermediate value of each third candidate node to the third angle parameter value respectively to obtain an updated fifth angle parameter value of each third candidate node.

In the embodiment of the present application, after obtaining the third intermediate value of each third candidate node, the encoder adds the third intermediate value of each third candidate node to the third angle parameter value of the first encoded node to obtain the updated fifth angle parameter value of each third candidate node; wherein the above process can be expressed as:
interPred.second[1]=prevPos[1]+qphi0*_geomAngularAzimuthSpeed;

Among them, prevPos[1] represents the third angle parameter value of the first encoded node, and interPred.second[1] represents the updated fifth angle parameter value of each third candidate node.

In some embodiments of the present application, if the local motion information of any third candidate node is greater than or equal to a first preset threshold, or the difference value is less than or equal to a second preset threshold, the fifth angle parameter value of any third candidate node is updated based on the local motion information of any third candidate node, and the updated fifth angle parameter value of any third candidate node is determined; the first preset threshold is greater than the second preset threshold.

In some embodiments of the present application, if the local motion information of any third candidate node is less than the first preset threshold and the local motion information is greater than the second preset threshold, the fifth angle parameter value of any third candidate node is not updated; the first preset threshold is greater than the second preset threshold.

In an embodiment of the present application, when the local motion information of any third candidate node is greater than or equal to the first preset threshold, or the local motion information is less than or equal to the second preset threshold, the encoder determines the updated fifth angle parameter value of any third candidate node based on the local motion information of any third candidate node; when the local motion information of any third candidate node is less than the first preset threshold and the local motion information is greater than the second preset threshold, the encoder uses the fifth angle parameter value of any third candidate node as the updated fifth angle parameter value of any third candidate node. The above process can be expressed as:
if(deltaPhi>=(_geomAngularAzimuthSpeed>>1)||deltaPhi<=-(_geomAngularAzimuthSpeed>>
1));

Among them, _geomAngularAzimuthSpeed>>1 means shifting right by one bit, that is, _geomAngularAzimuthSpeed multiplied by 0.5.

In some embodiments of the present application, the first preset threshold is Q times the rotation angular velocity, where Q is a positive number; and the second preset threshold is negative Q times the rotation angular velocity.

In the embodiment of the present application, Q is preset.

In the embodiment of the present application, Q is 0.5.

In some embodiments of the present application, the first candidate node includes a first reference node and a second reference node; the second candidate node includes a third reference node and a fourth reference node; the first reference node and the third reference node belong to a first reference frame; the second reference node and the fourth reference node belong to a second reference frame.

In the embodiment of the present application, the reference frame where the first reference node (node g) is located is the first reference frame; the reference frame where the second reference node (node b) is located is the second reference frame.

In the embodiment of the present application, based on FIG. 23, the third reference node may be at least one reference node other than the first reference node in the first reference frame, and the third reference node may be node e, node f, node o, and node p, and correspondingly, the preset node may be at least one of node e, node f, node o, and node p. The fourth reference node may be at least one reference node other than the second reference node in the second reference frame, and the fourth reference node may be node c, node d, node m, and node n, and correspondingly, the preset node may be at least one of node c, node d, node m, and node n. Alternatively, the preset node may be at least one of node c, node d, node m, node n, node e, node f, node o, and node p.

In some embodiments of the present application, determining at least one second candidate node in a reference frame according to the first candidate node may include:

determining a first reference node having a same radar index as the first encoded node in a second reference frame;

determining at least one third reference node in the first reference frame based on the first reference node;

determining a second reference node having the same radar index as the first encoded node in the first reference frame;

At least one fourth reference node is determined in the second reference frame according to the second reference candidate node.

It should be noted that the fourth angle parameter value of the first reference node is less than or equal to and closest to the third angle parameter value of the first encoded node; the sixth angle parameter value of at least one third reference node is greater than the fourth angle parameter value of the first reference node, and at least one third reference node has the same radar index as the first reference node; the fourth angle parameter value of the second reference node is less than or equal to and closest to the third angle parameter value of the first encoded node; the seventh angle parameter value of at least one fourth reference node is greater than the fourth angle parameter value of the second reference node, and at least one fourth reference node has the same radar index as the second reference node.

In some embodiments of the present application, determining at least one third reference node in the first reference frame according to the first reference node may include:

In the first reference frame, at least one third reference node that is sequentially encoded after the first reference node is determined according to the order of the prediction tree.

In the embodiment of the present application, based on FIG23 , the third reference node may include: node e, node f, node o, and node p. The first reference node may be node g.

Exemplarily, based on FIG. 23 , in the first reference frame, at least one of the nodes e, f, o, and p that are encoded sequentially after the first reference node (node g) is determined in the order of the prediction tree.

In some embodiments of the present application, determining at least one fourth reference node in the second reference frame according to the second reference candidate node may include:

In the second reference frame, at least one fourth reference node that is sequentially encoded after the second reference node is determined according to the order of the prediction tree.

In the embodiment of the present application, based on Figure 23, the fourth reference node may include: node c, node d, node m and node n. The second reference node may be node b.

Exemplarily, in the first reference frame, at least one of the nodes c, d, m and n that are encoded sequentially after the second reference node (node b) is determined in the order of the prediction tree.

In some embodiments of the present application, performing local motion processing on the angle parameter value of at least one candidate node in the at least one second candidate node to obtain the updated at least one second candidate node may include:

Determine local motion information of each third candidate node based on the fourth angle parameter value of the first reference node and the fifth angle parameter value of at least one third candidate node that matches the preset node in the at least one third reference node;

Based on the local motion information, the fifth angle parameter value of the corresponding third candidate node is updated to determine the updated fifth angle parameter value of at least one third candidate node, thereby determining the updated at least one third candidate node;

using, among the at least one updated third candidate node and the at least one third reference node, a candidate node other than the at least one third candidate node as the at least one updated third reference node;

The updated at least one third reference node and the at least one fourth reference node are used as the updated at least one second candidate node.

Exemplarily, based on FIG. 23, according to the first reference node (node g) in the first reference frame, the fifth angle parameter value of at least one third candidate node that matches the preset node (such as node e, node f) in at least one third reference node is subjected to local motion processing to determine the local motion information of each third candidate node. Among them, at least one third reference node may include: the first third reference node (node e), the second third reference node (node f), the third third reference node (node o) and the fourth third reference node (node p). At least one fourth reference node in the second reference frame may include: the first fourth reference node (node c), the second fourth reference node (node d), the third fourth reference node (node m) and the fourth fourth reference node (node n).

At this time, at least one third candidate node is: the first third reference node (node e) and the second third reference node (node f). The updated at least one third candidate node includes: the updated first third reference node (node e) and the updated second third reference node (node f). Further, the updated at least one third reference node includes: the updated first third reference node (node e), the updated second third reference node (node f), the third third reference node (node o) and the fourth third reference node (node p).

Further, based on Figure 23, the updated at least one second candidate node may include: the updated first third reference node (node e), the updated second third reference node (node f), the third third reference node (node o), the fourth third reference node (node p), the first fourth reference node (node c), the second fourth reference node (node d), the third fourth reference node (node m) and the fourth fourth reference node (node n).

In some embodiments of the present application, at least one third reference node, at least one updated fourth reference node, the second reference node, and the first reference node have a preset order.

It should also be noted that, in the embodiment of the present application, the preset order is not limited to this order, and may also be other orders, which are not specifically limited here. In addition, it should be noted that the order described here can be used as an optimal order to achieve the best encoding performance.

The determination of the first candidate node and at least one second candidate node and the preset order are described in detail below in conjunction with several specific implementations.

In a specific implementation manner, determining at least one second candidate node in a reference frame according to the first candidate node may include:

According to the coding order of the prediction tree, the first third reference node, the second third reference node, the third third reference node, and the fourth third reference node, which are coded after the first reference node, are sequentially determined in the first reference frame;

At least one third reference node is determined according to the first third reference node, the second third reference node, the third third reference node, and the fourth third reference node.

According to the coding order of the prediction tree, in the second reference frame, sequentially determine the first fourth reference node, the second fourth reference node, the third fourth reference node, and the fourth fourth reference node that are coded after the second reference node;

At least one fourth reference node is determined according to the first fourth reference node, the second fourth reference node, the third fourth reference node, and the fourth fourth reference node.

In an embodiment of the present application, FIG23 shows a schematic diagram of the structure of a geometric information inter-frame encoding and decoding provided by an embodiment of the present application. As shown in FIG23, the nodes to be encoded in the current frame are filled with a grid, and the previous encoded node of the node to be encoded (i.e., the first encoded node) is represented by a; there are a first reference frame and a second reference frame, wherein the second reference frame can be the previous frame of the current frame, and the first reference frame can be a GMC frame of the previous frame after global motion.

Exemplarily, taking FIG. 23 as an example, when performing inter-frame prediction coding on the node to be coded, first determine the previous coded node a of the current point;

Based on Figure 23, for the second reference frame (the previous frame of the current frame), the first candidate node b (i.e., the second reference node) having at least one identical geometric parameter (angle parameter value) as the previous encoded node a of the node to be encoded can be found in the second reference frame; then, according to the encoding order of the prediction tree, the first fourth reference node c, the second fourth reference node d, the second fourth reference node m and the fourth fourth reference node n encoded after the first candidate node b in the second reference frame are determined in sequence; among them, the first fourth reference node c, the second fourth reference node d, the second fourth reference node m and the fourth fourth reference node n are at least one second candidate node here (i.e., at least one fourth reference node).

Based on Figure 23, for the first reference frame (the GMC frame of the previous frame that has undergone global motion), the first candidate node g (i.e., the first reference node) having at least one identical geometric parameter (angle parameter value) with the previous encoded node a of the node to be encoded can be found in the first reference frame; then, according to the encoding order of the prediction tree, the first third reference node e, the second third reference node f, the third third reference node o, and the fourth third reference node p encoded after the first candidate node g in the first reference frame are determined in sequence; wherein, the first third reference node e, the second third reference node f, the third third reference node o, and the fourth third reference node p are at least one second candidate node (i.e., the third reference node) here. It should be noted that the horizontal azimuth angles of the first third reference node e, the second third reference node f, the third third reference node o, and the fourth third reference node p here may not be replaced or may also be replaced, wherein, here, it may be replaced with the horizontal azimuth angle of the father node of the node to be encoded, or it may also be replaced with the horizontal azimuth angle after local motion processing.

In another specific implementation, determining at least one second candidate node in a reference frame according to the first candidate node may include:

According to the order of the magnitude of the horizontal azimuth angles, determine in the second reference frame in sequence the first fourth reference node whose horizontal azimuth angle is greater than and closest to the horizontal azimuth angle of the second reference node, the second fourth reference node whose horizontal azimuth angle is greater than and closest to the horizontal azimuth angle of the first fourth reference node, the third fourth reference node whose horizontal azimuth angle is greater than and closest to the horizontal azimuth angle of the second fourth reference node, and the fourth fourth reference node whose horizontal azimuth angle is greater than and closest to the horizontal azimuth angle of the third fourth reference node;

At least one second candidate node (i.e., fourth reference node) is determined based on the first fourth reference node, the second fourth reference node, the third fourth reference node, and the fourth fourth reference node; wherein the radar laser index values of the first fourth reference node, the second fourth reference node, the third fourth reference node, and the fourth fourth reference node are all the same as the radar laser index value of the previous encoded node.

In the embodiment of the present application, as shown in FIG. 23 , it is assumed that at least one second candidate node (i.e., the fourth reference node) includes the first fourth reference node c, the second fourth reference node d, the third fourth reference node m, and the fourth fourth reference node n. When performing inter-frame prediction coding on the node to be coded, first determine the previous coded node a of the current point; then determine the second reference node b having the same angle parameter value as the previous coded node a; and then determine the second reference node b according to the horizontal azimuth angle. The order of size is determined as follows:

Determine in the second reference frame the first fourth reference node c having the same radar laser index number and a first horizontal azimuth angle (i.e., an angle parameter value) greater than the horizontal azimuth angle of the second reference node b;

Determine in the second reference frame a second fourth reference node d having the same radar laser index number and a first horizontal azimuth angle greater than the horizontal azimuth angle of the first fourth reference node c;

Determine in the second reference frame a third fourth reference node m having the same radar laser index number and a first horizontal azimuth angle greater than the horizontal azimuth angle of the second fourth reference node d;

Determine in the second reference frame a fourth fourth reference node n having the same radar laser index serial number and a first horizontal azimuth angle greater than and closest to the horizontal azimuth angle of the third fourth reference node m;

At this time, the first fourth reference node c, the second fourth reference node d, the third fourth reference node m and the fourth fourth reference node The fourth reference node n is at least one second candidate node (ie, the fourth reference node) here.

In another specific implementation, determining at least one second candidate node in a reference frame according to the first candidate node may include:

According to the order of the horizontal azimuth angles, determine in the first reference frame, in sequence, the first third reference node whose horizontal azimuth angle is greater than and closest to the horizontal azimuth angle of the first candidate node (i.e., the first reference node), the second third reference node whose horizontal azimuth angle is greater than and closest to the horizontal azimuth angle of the first third reference node, the third third reference node whose horizontal azimuth angle is greater than and closest to the horizontal azimuth angle of the second third reference node, and the fourth third reference node whose horizontal azimuth angle is greater than and closest to the horizontal azimuth angle of the third third reference node;

At least one second candidate node (i.e., at least one third reference node) is determined based on the first third reference node, the second third reference node, the third third reference node, and the fourth third reference node; wherein the radar laser index numbers of the first third reference node, the second third reference node, the third third reference node, and the fourth third reference node are all the same as the radar laser index number of the previous encoded node.

In the embodiment of the present application, as shown in FIG23, it is assumed that at least one second candidate node includes the first third reference node e, the second third reference node f, the third third reference node o and the fourth third reference node p. When performing inter-frame prediction coding on the node to be coded, first determine the previous coded node a of the node to be coded; then determine the third candidate node g (first reference node) having the same angle parameter value as the previous coded node a; and then determine the third candidate node g (first reference node) according to the horizontal azimuth angle. The order of size is as follows:

Determine in the first reference frame the first third reference node e having the same radar laser index number and a first horizontal azimuth angle greater than the horizontal azimuth angle of the first candidate node g (i.e., the first reference node);

Determine in the first reference frame a second third reference node f having the same radar laser index number and a first horizontal azimuth angle greater than the horizontal azimuth angle of the first third reference node e;

Determine in the first reference frame a third third reference node o having the same radar laser index number and a first horizontal azimuth angle greater than the horizontal azimuth angle of the second third reference node f;

Determine in the first reference frame a fourth third reference node p having the same radar laser index number and a first horizontal azimuth angle greater than the horizontal azimuth angle of the third third reference node o;

At this time, the obtained first third reference node e, second third reference node f, third third reference node o and fourth third reference node p are at least one second candidate node (ie, third reference node) here.

It should also be noted that, based on Figure 23, the preset order can be: the 1st fourth reference node c, the 2nd fourth reference node d, the 1st third reference node e, the 2nd third reference node f, the 3rd fourth reference node m, the 4th fourth reference node n, the 3rd third reference node o and the 3rd third reference node p.

Based on Figure 23, the preset order can also be: the first fourth reference node c, the second fourth reference node d, the first third reference node e, the second third reference node f, the third fourth reference node m and the fourth fourth reference node n.

Based on Figure 23, the preset order can also be: the first fourth reference node c, the second fourth reference node d, the first third reference node e, the second third reference node f, the third fourth reference node m, the fourth fourth reference node n, the second reference node b and the first reference node g.

In an embodiment of the present application, cost values are calculated for the first candidate node and each updated second candidate node, respectively, to obtain multiple rate-distortion cost results; the candidate node corresponding to the minimum rate-distortion cost among the multiple rate-distortion cost results is determined as the prediction node; based on the prediction node, the geometric prediction value of the node to be encoded is determined.

In some embodiments of the present application, the method may further include: determining a predicted node index value corresponding to the node to be encoded in a preset order; encoding the predicted node index value, and writing the obtained encoded bits into a bitstream.

In some embodiments of the present application, the method may further include: determining geometric residual information of the node to be encoded based on the geometric prediction value of the node to be encoded; encoding the geometric residual information of the node to be encoded, and writing the obtained encoded bits into the bitstream.

In some embodiments of the present application, determining the geometric residual information of the node to be encoded based on the geometric prediction value of the node to be encoded may include: determining the initial residual value of the node to be encoded based on the geometric prediction value of the node to be encoded; quantizing the initial residual value of the node to be encoded based on a quantization parameter to obtain the geometric residual information of the node to be encoded.

In some embodiments of the present application, determining an initial residual value of a node to be encoded based on a geometric prediction value of the node to be encoded may include: determining the original value of the node to be encoded; and determining the initial residual value of the node to be encoded by performing a subtraction operation between the original value of the node to be encoded and the geometric prediction value of the node to be encoded.

In some embodiments of the present application, the method may further include: encoding the quantization parameter, and writing the obtained encoded bits into a bit stream.

For example, taking the geometric position information as an example, first determine the geometric prediction value of the node to be encoded; then perform a difference operation based on the geometric position information of the current node and the geometric prediction value to obtain an initial residual value; and use the quantization parameter to quantize the initial residual value. Finally, through continuous iteration, the inter-frame prediction mode value, geometric prediction residual value, prediction tree structure, quantization parameter and other parameters of each node position information in the prediction tree are encoded, and the obtained coded bits are written into the bitstream.

Furthermore, in the embodiment of the present application, the encoding method is mainly for encoding optimization of the inter-frame prediction mode. Here, it can also be determined whether the node to be encoded uses the inter-frame prediction mode, and a flag is generated to identify it. Therefore, in some embodiments, the method can also include:

Determine a prediction mode of the node to be encoded, and generate first identification information based on the prediction mode; the first identification information indicates whether the node to be encoded uses an inter-frame prediction mode;

When the prediction mode is the inter-frame prediction mode, a step of determining a first encoded node before the node to be encoded in the current frame is performed.

Further, with respect to the first identification information, in some embodiments, determining the first identification information may include:

If the first identification information indicates that the node to be encoded does not use the inter-frame prediction mode, determining that the value of the first identification information is a first value;

If the first identification information indicates that the node to be encoded uses the inter-frame prediction mode, then the value of the first identification information is determined to be the second value

It should be noted that in the embodiment of the present application, the first value is different from the second value, and the first value and the second value can be in parameter form or in digital form. Specifically, the first identification information can be a parameter written in the profile or a flag value, which is not specifically limited here.

Exemplarily, for the first value and the second value, the first value can be set to 1 and the second value can be set to 0; or, the first value can be set to 0 and the second value can be set to 1; or, the first value can be set to true and the second value can be set to false; or, the first value can be set to false and the second value can be set to true; but this is not specifically limited here.

In some embodiments, the method may further include: encoding the first identification information, and writing the obtained encoded bits into a bit stream.

It should also be noted that, in the embodiment of the present application, taking the flag written into the bitstream as an example, assuming that the first value is 0 and the second value is 1, if it is determined that the current node does not use the inter-frame prediction mode, the first identification information (0) is generated; if it is determined that the current node uses the inter-frame prediction mode, the first identification information (1) is generated. In this way, at the decoding end, by decoding and obtaining the first identification information, it is possible to determine whether the current node uses the inter-frame prediction mode, thereby improving decoding efficiency.

Furthermore, in some embodiments of the present application, a flag bit may be set to determine whether to enable the encoding method of the embodiment of the present application. Therefore, in some embodiments, the method may further include:

Determine whether to enable the local motion processing mode, and generate second identification information; the second identification information indicates whether the local motion processing mode is enabled for the node to be encoded;

When it is determined that the local motion processing mode is enabled for the node to be encoded, a step of determining a first encoded node before the node to be encoded in the current frame is performed.

Further, with respect to the second identification information, in some embodiments, determining the second identification information may include:

If the second identification information indicates that the node to be encoded does not enable the local motion processing mode, determining the value of the second identification information to be the first value;

If the second identification information indicates that the node to be encoded enables the local motion processing mode, the value of the second identification information is determined to be the second value.

It should be noted that in the embodiment of the present application, the first value is different from the second value, and the first value and the second value can be in parameter form or in digital form. Specifically, the second identification information can be a parameter written in the profile or a flag value, which is not specifically limited here.

Exemplarily, for the first value and the second value, the first value can be set to 1, and the second value can be set to 0; or, the first value can be set to 0, and the second value can be set to 1; or, the first value can be set to true, and the second value can be set to false; or, the first value can be set to false, and the second value can be set to true; but this is not specifically limited here.

Furthermore, in some embodiments of the present application, the method may also include: encoding the value of the second identification information, and writing the obtained encoded bits into the bit stream.

It should also be noted that, in the embodiment of the present application, taking the flag written into the bitstream as an example, assuming that the first value is 0 and the second value is 1, if it is determined that the local motion processing mode is not enabled for the current node, the second identification information (0) is generated; if it is determined that the local motion processing mode is not enabled for the current node, the second identification information (1) is generated. In this way, the value of the second identification information can be directly obtained by decoding at the decoding end, so as to determine whether the current node is enabled, thereby improving the decoding efficiency.

In short, in the embodiment of the present application, a 1-bit flag (i.e., the second identification information) can be used to indicate whether the encoding method of the embodiment of the present application is enabled or not. This flag can be placed in the header information of the high-level syntax element, such as the geometry header; and this flag can be conditionally enabled under certain conditions. If this flag does not appear in the bitstream, its default value is a fixed value.

This embodiment provides an encoding method, wherein an encoder first determines a first encoded node preceding a node to be encoded in a current frame; then, the encoder determines a first candidate node having at least one geometric parameter identical to the first encoded node in a reference frame, At least one second candidate node is determined in the reference frame according to the first candidate node; then, the encoder performs local motion processing on the angle parameter value of at least one candidate node in the at least one second candidate node to obtain at least one updated second candidate node; finally, the encoder determines the geometric prediction value of the node to be encoded based on the first candidate node and the at least one updated second candidate node. Since the encoder performs local motion processing on the angle parameter value of at least one candidate node in the at least one second candidate node, at least one candidate node in the at least one second candidate node has prior information related to local motion, so that inter-frame prediction can better predict the node to be encoded, thereby improving the accuracy of inter-frame prediction, improving the encoding efficiency of geometric information, and further improving the encoding performance of point cloud.

In another embodiment of the present application, based on the encoding/decoding method described in the aforementioned embodiment, since the related technology only considers the prior information of global motion when performing inter-frame prediction on the selected inter-frame prediction candidate points, the embodiment of the present application mainly performs local motion processing on the angle parameter value of the prediction node, which can improve the accuracy of inter-frame prediction, thereby improving the encoding and decoding efficiency of the geometric information of the point cloud and improving the encoding and decoding performance of the point cloud.

In the embodiment of the present application, the tool proposed in the present application can use a 1-bit flag to indicate whether it is enabled or not. This flag is placed in the header information of the high-level syntax element, such as the geometry header, and this flag is conditionally enabled under certain conditions. If this flag does not appear in the bitstream, its default value is a fixed value. Similarly, the flag needs to be decoded at the decoding end. If this flag does not appear in the bitstream, it can be decoded without decoding, and its default value is a fixed value.

The above point cloud encoding and decoding method is explained in detail below in some specific embodiments.

Example 1 (10 points):

In a possible implementation, taking FIG. 23 as an example, at the encoding end, when performing inter-frame predictive encoding on the current point to be encoded (point to be encoded), the prediction tree (i.e., in the order of the prediction tree) is traversed, and the previous encoded node a (the first encoded node) of the current point to be encoded (node to be encoded) is searched; the previous frame is used as a reference frame (the second reference frame) to find the node a that has the same encoding as the previous encoded node a of the current point. (third angle parameter value) and point b (the second reference node or the first candidate node) of laserID, point b in the reference frame of the previous frame and point c (the first fourth reference node) and point d (the second fourth reference node) and point m (the third fourth reference node) and point n (the fourth fourth reference node) encoded or decoded after point b are used as candidate points between frames.

In one possible implementation, the previous frame is used as a reference frame to find a node a that has the same laser ID as the node a that has been encoded before the current point is encoded and the first point Less than or equal to point a Point b, and/or

In the previous frame as the reference frame, find the node a that has the same laserID as the node a that has been encoded before the current point and the first point Greater than point a Point c, and/or

In the previous frame as the reference frame, find the node a that has the same laserID as the node a that has been encoded before the current point and the first point Greater than point c point d, and/or

In the previous frame as the reference frame, find the node a that has the same laserID as the node a that has been encoded before the current point and the first point Greater than point d point m, and/or

In the previous frame as the reference frame, find the node a that has the same laserID as the node a that has been encoded before the current point and the first point Greater than point m point n, and/or,

Point b in the previous reference frame and points c, d, m and n encoded or decoded after point b are used as candidate points between frames.

In a possible implementation, a node a (first coded node) having the same eigenvalue as the node a that has been coded before the current point is coded is searched in a reference frame (first reference frame) that has undergone global motion in the previous frame. And point g (the first reference node or the first candidate node) of laserID, take the point g in the previous frame after global motion as the reference frame and the point e (the first third reference node), point f (the second third reference node), point o (the third third reference node) and point p (the fourth third reference node) encoded or decoded after point g as candidate points between frames.

In one possible implementation, the previous frame is used as a reference frame to find a node a that has the same laser ID as the node a that has been encoded before the current point is encoded and the first point Less than or equal to point a point g, and/or,

In the previous frame as the reference frame, find the node a that has the same laserID as the node a that has been encoded before the current point and the first point Greater than point a point e, and/or,

In the previous frame as the reference frame, find the node a that has the same laserID as the node a that has been encoded before the current point and the first point Greater than point e The point f, and/or

In the previous frame as the reference frame, find the node a that has the same laserID as the node a that has been encoded before the current point and the first point Greater than point f o, and/or

In the previous frame as the reference frame, find the node a that has the same laserID as the node a that has been encoded before the current point and the first point Greater than point o point p, and/or

The point g in the previous frame that has undergone global motion is used as the reference frame, and the points e, f, o, and p that are encoded or decoded after point g are used as candidate points between frames.

At the same time, the inter-frame prediction points e, f, o, p Replace it with the following local motion:

First calculate the points e, f, o, p Minus the g get (local motion information);

if The value is greater than or equal to k times (k is 0.5) the angular azimuth speed or The value is less than or equal to negative k times (k is 0.5) the value of angular azimuth speed or proceed to the following steps without making any judgment:

calculate Indicates rounding up. This application does not limit and can also round down.

The inter-frame prediction points e, f, o, p Replace with point a Add qphi0*angular azimuth speed.

Some pseudo code of the above process is as follows:
auto deltaPhi=interPred.second[1]-interPredPrev.second[1;
if(
deltaPhi>=(_geomAngularAzimuthSpeed>>1)
||deltaPhi<=-(_geomAngularAzimuthSpeed>>1)){
int qphi0＝divApprox(
int64_t(deltaPhi)+(_geomAngularAzimuthSpeed>>1),
_geomAngularAzimuthSpeed,0);
interPred.second[1]＝
prevPos[1]+qphi0*_geomAngularAzimuthSpeed;
}

In this way, different prediction points (including several candidate points within a frame and at most 10 candidate points between frames) are selected through RDO rate-distortion optimization, namely, node c, node d, node e, node f, node m, node n, node o, node p, node b and node g.

Among them, there are requirements for the order of candidate prediction points, specifically:

In the order of c, d, e, f, m, n, o, p, b, and g (this is the optimal order, which can achieve the best performance, and other orders are also possible), RDO rate-distortion optimization is performed to select the optimal inter-frame prediction point.

Furthermore, to select the inter-frame prediction mode as c or d or m or n or b corresponding to a parameter of a selected contex model context model, to select the inter-frame prediction mode as e or f or o or p or g corresponding to another parameter of another selected contex model context model, the subsequent entropy encoding/decoding of the residual coefficients is performed.

After determining the prediction node, the geometric position information of the prediction node is predicted to obtain the prediction residual, and the geometric prediction residual is quantized using the quantization parameter. Finally, through continuous iteration, the prediction mode, prediction residual, prediction tree structure, quantization parameter and other parameters of the prediction tree node position information are encoded to generate a binary code stream.

In a possible implementation, at the decoding end, the decoding end reconstructs the prediction tree structure by continuously parsing the bitstream, and traverses the prediction tree for the previous decoded node a of the current point to be decoded;

First, decode the prediction mode;

Among them, there are requirements for the order of candidate prediction points, specifically:

According to the decoded prediction mode, inter-frame prediction points are selected in the order of nodes c, d, e, f, m, n, o, p, b, and g (this is the optimal order, which can achieve the best performance, and other orders are also possible).

In a possible implementation, if the prediction mode is an inter-frame prediction mode, the decoded inter-frame prediction mode may be used to determine a prediction point from the following at most 10 candidate nodes:

In the previous frame as the reference frame, find the node a (the first decoded node) that has the same (third angle parameter value) and point b (the second decoded node) of laserID, point b in the previous reference frame (the second reference frame) and points c, d, m and n encoded or decoded after point b are used as candidate points between frames.

In one possible implementation, the previous frame is used as a reference frame to find a node a that has the same laser ID as the node a that has been encoded before the current point is encoded and the first point Less than or equal to point a Point b;

In the previous frame as the reference frame, find the node a that has the same laserID as the node a that has been encoded before the current point and the first point Greater than point b Point c;

In the previous frame as the reference frame, find the node a that has the same laserID as the node a that has been encoded before the current point and the first point Greater than point c point d;

In the previous frame as the reference frame, find the node a that has the same laserID as the node a that has been encoded before the current point and the first point Greater than point d Point m;

In the previous frame as the reference frame, find the node a that has the same laserID as the node a that has been encoded before the current point and the first point Greater than point m point n.

Point b in the previous frame reference frame and points c, d, m and n encoded or decoded after point b are used as candidates for inter-frame point;

In a possible implementation, a node a (first decoded node) having the same vertices as the node a that has been decoded before the current point is searched in a reference frame (first reference frame) that has undergone global motion in the previous frame. and point g (the second decoded node) of laserID, and take point g in the previous frame after global motion as the reference frame and point e, point f, point o and point p encoded or decoded after point g as candidate points between frames.

In one possible implementation, the previous frame is used as a reference frame to find a node a that has the same laser ID as the node a that has been encoded before the current point is encoded and the first point Less than or equal to point a point g;

In the previous frame as the reference frame, find the node a that has the same laserID as the node a that has been encoded before the current point and the first point Greater than point a point e;

In the previous frame as the reference frame, find the node a that has the same laserID as the node a that has been encoded before the current point and the first point Greater than point e Point f;

In the previous frame as the reference frame, find the node a that has the same laserID as the node a that has been encoded before the current point and the first point Greater than point f Point o;

In the previous frame as the reference frame, find the node a that has the same laserID as the node a that has been encoded before the current point and the first point Greater than point o Point p;

The point g in the previous frame that has undergone global motion is used as the reference frame, and the points e, f, o, and p that are encoded or decoded after point g are used as candidate points between frames.

At the same time, the inter-frame prediction points e, f, o, p Replace it with a local motion method.

Furthermore, the geometric position prediction residual information and quantization parameters of the prediction node are obtained through analysis, and the prediction residual is dequantized to restore the reconstructed geometric position information of each node, and finally the geometric reconstruction at the decoding end is completed.

Example 2 (6 points):

In a possible implementation, taking FIG. 24 as an example, at the encoding end, when performing inter-frame predictive encoding on the current point to be encoded, the previous encoded node a of the current point to be encoded in the prediction tree is traversed;

In the previous frame as the reference frame, search for point b with the same φ and laserID as the node a that has been encoded before the current point, and take points c, d, m and n that are encoded or decoded after point b in the previous frame as candidate points between frames.

In one possible implementation, the previous frame is used as a reference frame to find a node a that has the same laser ID as the node a that has been encoded before the current point is encoded and the first point Greater than point a Point c, and/or

In the previous frame as the reference frame, find the node a that has the same laserID as the node a that has been encoded before the current point and the first point Greater than point c point d, and/or

In the previous frame as the reference frame, find the node a that has the same laserID as the node a that has been encoded before the current point and the first point Greater than point d point m, and/or

In the previous frame as the reference frame, find the node a that has the same laserID as the node a that has been encoded before the current point and the first point Greater than point m point n, and/or,

Points c, d, m and n encoded or decoded after point b in the previous reference frame are used as candidate points between frames;

In a possible implementation, a node a which has been encoded before the current point is searched in the previous frame which has been globally moved as a reference frame and has the same and point g of laserID, and take the points e and f encoded or decoded after point g in the previous frame after global motion as the reference frame as candidate points between frames.

In one possible implementation, the previous frame is used as a reference frame to find a node a that has the same laser ID as the node a that has been encoded before the current point is encoded and the first point Less than or equal to point a point g, and/or,

In the previous frame as the reference frame, find the node a that has the same laserID as the node a that has been encoded before the current point and the first point Greater than point a point e, and/or,

In the previous frame as the reference frame, find the node a that has the same laserID as the node a that has been encoded before the current point and the first point Greater than point e The point f, and/or

The points e and f encoded or decoded after the global motion of the previous frame as the point g in the reference frame are used as candidate points between frames.

At the same time, the inter-frame prediction points e and f Replace it with a local motion method.

In this way, different prediction points (including several candidate points within a frame and at most 6 candidate points between frames) are selected through RDO rate-distortion optimization, namely, node c, node d, node e, node f, node m and node n.

Among them, there are requirements for the order of candidate prediction points, specifically:

According to the order of nodes c, d, e, f, m, and n (this is the optimal order, which can achieve the best performance, and other orders are also possible), RDO rate-distortion optimization is performed to select the optimal inter-frame prediction point.

Furthermore, for selecting the inter-frame prediction mode as c or d or m or n or b, a context model is selected. Parameters, select the inter-frame prediction mode e or f corresponding to another selection of contex model parameters of another context model to perform the subsequent entropy encoding/decoding of the residual coefficients.

After determining the prediction node, the geometric position information of the prediction node is predicted to obtain the prediction residual, and the geometric prediction residual is quantized using the quantization parameter. Finally, through continuous iteration, the prediction mode, prediction residual, prediction tree structure, quantization parameter and other parameters of the prediction tree node position information are encoded to generate a binary code stream.

In a possible implementation, at the decoding end, the decoding end reconstructs the prediction tree structure by continuously parsing the bitstream, and traverses the prediction tree for the previous decoded node a of the current point to be decoded;

First, decode the prediction mode;

Among them, there are requirements for the order of candidate prediction points, specifically:

According to the decoded prediction mode, inter-frame prediction points are selected in the order of nodes c, d, e, f, m, and n (this is the optimal order, which can achieve the best performance, and other orders are also possible).

If the prediction mode is an inter-frame prediction mode, the decoded inter-frame prediction mode can be used to determine the prediction point from the following at most 6 candidate nodes:

In a possible implementation, the previous frame is used as a reference frame to find a node a that has the same and point b of laserID, and take points c, d, m and n encoded or decoded after point b in the previous reference frame as candidate points between frames.

In one possible implementation, the previous frame is used as a reference frame to find a node a that has the same laser ID as the node a that has been encoded before the current point is encoded and the first point Greater than point a Point c;

In the previous frame as the reference frame, find the node a that has the same laserID as the node a that has been encoded before the current point and the first point Greater than point c point d;

In the previous frame as the reference frame, find the node a that has the same laserID as the node a that has been encoded before the current point and the first point Greater than point d Point m;

In the previous frame as the reference frame, find the node a that has the same laserID as the node a that has been encoded before the current point and the first point Greater than point m Point n;

Points c, d, m and n encoded or decoded after point b in the previous reference frame are used as candidate points between frames.

In a possible implementation, a node a that has been decoded before the current point is searched in the previous frame that has undergone global motion as a reference frame and has the same and point g of laserID, and take the points e and f encoded or decoded after point g in the previous frame after global motion as the reference frame as candidate points between frames.

In one possible implementation, the previous frame is used as a reference frame to find a node a that has the same laser ID as the node a that has been encoded before the current point is encoded and the first point Less than or equal to point a point g;

In the previous frame as the reference frame, find the node a that has the same laserID as the node a that has been encoded before the current point and the first point Greater than point a point e;

In the previous frame as the reference frame, find the node a that has the same laserID as the node a that has been encoded before the current point and the first point Greater than point e Point f;

The points e and f encoded or decoded after the global motion of the previous frame as the point g in the reference frame are used as candidate points between frames.

At the same time, the inter-frame prediction points e and f Replace it with a local motion method.

Furthermore, the geometric position prediction residual information and quantization parameters of the prediction node are obtained through analysis, and the prediction residual is dequantized to restore the reconstructed geometric position information of each node, and finally the geometric reconstruction at the decoding end is completed.

The specific test results are shown in the following table. See Table 1-1, which shows the test results of a geometric position lossless and attribute lossless case provided by the embodiment of the present application; see Table 1-2, which shows the test results of a geometric position lossy and attribute lossy case provided by the embodiment of the present application. It can be seen that the encoding and decoding performance is improved.

Table 1-1

Table 1-2

Example 3 (8 points):

In a possible implementation, taking FIG. 23 as an example, at the encoding end, when performing inter-frame predictive encoding on the current point to be encoded, the previous encoded node a of the current point to be encoded in the prediction tree is traversed;

In the previous frame as the reference frame, find the node a that has the same and point b of laserID, and take points c, d, m and n encoded or decoded after point b in the reference frame of the previous frame as candidate points between frames.

In one possible implementation, the previous frame is used as a reference frame to find a node a that has the same laser ID as the node a that has been encoded before the current point is encoded and the first point Less than or equal to point a point g;

In the previous frame as the reference frame, find the node a that has the same laserID as the node a that has been encoded before the current point and the first point Greater than point a point e;

In the previous frame as the reference frame, find the node a that has the same laserID as the node a that has been encoded before the current point and the first point Greater than point e Point f;

In the previous frame as the reference frame, find the node a that has the same laserID as the node a that has been encoded before the current point and the first point Greater than point f Point o;

In the previous frame as the reference frame, find the node a that has the same laserID as the node a that has been encoded before the current point and the first point Greater than point o Point p.

Points e, f, o and p encoded or decoded after point g in the previous frame after global motion are used as candidate points between frames.

At the same time, the inter-frame prediction points e, f, o, p Replace it with a local motion method.

In this way, different prediction points (including several candidate points within a frame and at most 8 candidate points between frames) are selected through RDO rate-distortion optimization, namely, node c, node d, node e, node f, node m and node n.

Among them, there are requirements for the order of candidate prediction points, specifically:

According to the order of nodes c, d, e, f, m, n, o, and p (this is the optimal order, which can achieve the best performance, and other orders are also possible), RDO rate-distortion optimization is performed to select the optimal inter-frame prediction point.

Furthermore, to select the inter-frame prediction mode as c or d or m or n or b corresponding to a parameter of a selected contex model context model, to select the inter-frame prediction mode as e or f or o or p corresponding to another parameter of another selected contex model context model, the subsequent entropy encoding/decoding of the residual coefficients is performed.

After determining the prediction node, the geometric position information of the prediction node is predicted to obtain the prediction residual, and the geometric prediction residual is quantized using the quantization parameter. Finally, through continuous iteration, the prediction mode, prediction residual, prediction tree structure, quantization parameter and other parameters of the prediction tree node position information are encoded to generate a binary code stream.

In a possible implementation, at the decoding end, the decoding end reconstructs the prediction tree structure by continuously parsing the bitstream, and traverses the prediction tree for the previous decoded node a of the current point to be decoded;

First, decode the prediction mode;

Among them, there are requirements for the order of candidate prediction points, specifically:

According to the decoded prediction mode, the order of nodes c, d, e, f, m, n, o, p is used (this is the optimal order, which can achieve the best result). The inter-frame prediction points are selected in other orders to obtain the best performance.

If the prediction mode is an inter-frame prediction mode, the decoded inter-frame prediction mode can be used to determine the prediction point from the following up to 8 candidate nodes:

In a possible implementation, the previous frame is used as a reference frame to find a node a that has the same and point b of laserID, and take points c, d, m and n encoded or decoded after point b in the previous reference frame as candidate points between frames.

In one possible implementation, the previous frame is used as a reference frame to find a node a that has the same laser ID as the node a that has been encoded before the current point is encoded and the first point Greater than point a Point c,

In the previous frame as the reference frame, find the node a that has the same laserID as the node a that has been encoded before the current point and the first point Greater than point c Point d,

In the previous frame as the reference frame, find the node a that has the same laserID as the node a that has been encoded before the current point and the first point Greater than point d Point m,

In the previous frame as the reference frame, find the node a that has the same laserID as the node a that has been encoded before the current point and the first point Greater than point m Point n,

Points c, d, m and n encoded or decoded after point b in the previous reference frame are used as candidate points between frames.

In a possible implementation, a node a that has been decoded before the current point is searched in the previous frame that has undergone global motion as a reference frame and has the same and point g of laserID, and use the points e and f, o and p encoded or decoded after point g in the previous frame after global motion as the reference frame as candidate points between frames.

In one possible implementation, the previous frame is used as a reference frame to find a node a that has the same laser ID as the node a that has been encoded before the current point is encoded and the first point Less than or equal to point a point g;

In the previous frame as the reference frame, find the node a that has the same laserID as the node a that has been encoded before the current point and the first point Greater than point a point e;

In the previous frame as the reference frame, find the node a that has the same laserID as the node a that has been encoded before the current point and the first point Greater than point e Point f;

In the previous frame as the reference frame, find the node a that has the same laserID as the node a that has been encoded before the current point and the first point Greater than point f Point o;

In the previous frame as the reference frame, find the node a that has the same laserID as the node a that has been encoded before the current point and the first point Greater than point o Point p.

The points e, f, o, and p encoded or decoded after the global motion of the previous frame as the reference frame point g are used as candidate points between frames.

At the same time, the inter-frame prediction points e, f, o, p Replace it with a local motion method.

Furthermore, the geometric position prediction residual information and quantization parameters of the prediction node are obtained through analysis, and the prediction residual is dequantized to restore the reconstructed geometric position information of each node, and finally the geometric reconstruction at the decoding end is completed.

The specific test results are shown in the following table. See Table 2-1, which shows the test results of a geometric position lossless and attribute lossless case provided by the embodiment of the present application; see Table 2-2, which shows the test results of a geometric position lossy and attribute lossy case provided by the embodiment of the present application. It can be seen that the encoding and decoding performance is improved.

Table 2-1

Table 2-2

It can be seen that by introducing the prior information of local motion, the compression performance under lossy or lossless conditions can be significantly improved.

It should also be noted that, in the embodiments of the present application, the reference frame can be the previous frame or the previous K frames, where K is a positive integer; alternatively, in the first reference frame or the second reference frame, the number of selected candidate nodes can continue to increase; alternatively, the average can be taken between every several candidate nodes to form a new candidate node, which is not specifically limited here.

In the embodiments of the present application, the specific implementation of the aforementioned embodiments is elaborated in detail through the above embodiments. It can be seen that according to the technical scheme of the aforementioned embodiments, the prediction scheme between frames of the geometric prediction tree is improved here. The core is that when obtaining the inter-frame prediction point, the local motion information of the motion between the inter-frame points is calculated, and the prior local motion information is used to perform better inter-frame prediction on the current point to be encoded.

In one embodiment of the present application, a code stream is provided, wherein the code stream is generated by bit encoding according to information to be encoded; wherein the information to be encoded includes at least one of the following:

The geometric prediction residual value, quantization parameter, prediction node index value, first identification information and second identification information of the node to be encoded;

The first identification information is used to indicate whether the node to be encoded uses an inter-frame prediction mode, and the second identification information is used to indicate whether the node to be encoded enables a local motion processing mode.

In another embodiment of the present application, based on the same inventive concept as the above-mentioned embodiment, see FIG25, which shows a schematic diagram of the composition structure of a decoder provided by the embodiment of the present application. As shown in FIG25, the decoder 20 includes a decoding unit 21, a first determination unit 22 and a first local motion processing unit 23; wherein,

The decoding unit 21 is configured to parse the bitstream, determine the predicted node index value corresponding to the node to be decoded; and determine the first decoded node before the node to be decoded in the current frame;

The first determining unit 22 is configured to determine a prediction node according to the prediction node index value and the first decoded node;

The first local motion processing unit 23 is configured to perform local motion processing on the first angle parameter value of the prediction node based on the first decoded node to determine the second angle parameter value of the prediction node;

The first determination unit 22 is further configured to determine the geometric parameters of the predicted node based on the first angle parameter value or the second angle parameter value; and determine the geometric prediction value of the node to be decoded based on the geometric parameters.

In some embodiments of the present application, the first local motion processing unit 23 is further configured to determine the local motion information based on the fourth angle parameter value of the second decoded node and the first angle parameter value of the predicted node, when the predicted node index value represents that the predicted node is a preset node; the fourth angle parameter value of the second decoded node is less than or equal to and closest to the third angle parameter value of the first decoded node; the second decoded node is determined based on the first decoded node in the reference frame where the predicted node is located; and the second angle parameter value of the predicted node is determined based on the local motion information.

In some embodiments of the present application, the reference frame where the prediction node is located includes: a first reference frame and a second reference frame; the first reference frame is at least one frame obtained by performing global motion on the second reference frame; the second reference frame is a decoded frame of the previous K frames of the current frame, where K is an integer greater than 0.

In some embodiments of the present application, the preset node is at least one decoded node in the first reference frame except the second decoded node.

In some embodiments of the present application, the first local motion processing unit 23 is further configured to determine a difference value between a fourth angle parameter value of the second decoded node and the first angle parameter value of the predicted node as the local motion information.

In some embodiments of the present application, the first local motion processing unit 23 is further configured to determine the rotation angular velocity of the laser radar corresponding to the node to be decoded; based on the local motion information, the third angle parameter value and the rotation angular velocity, determine the The second angle parameter value.

In some embodiments of the present application, the first local motion processing unit 23 is also configured to determine a first intermediate value based on the ratio of the local motion information to the rotation angular velocity; round the first intermediate value to obtain a second intermediate value; multiply the second intermediate value by the rotation angular velocity to obtain a third intermediate value; add the third intermediate value to the third angle parameter value to obtain the second angle parameter value.

In some embodiments of the present application, the first local motion processing unit 23 is also configured to determine the second angle parameter value of the prediction node based on the local motion information if the local motion information is greater than or equal to a first preset threshold, or the difference value is less than or equal to a second preset threshold; the first preset threshold is greater than the second preset threshold.

In some embodiments of the present application, the first local motion processing unit 23 is further configured to determine the first angle parameter value as the second angle parameter value if the local motion information is less than a first preset threshold and the local motion information is greater than a second preset threshold; the first preset threshold is greater than the second preset threshold.

In some embodiments of the present application, the first preset threshold is Q times the rotation angular velocity, where Q is a positive number; and the second preset threshold is negative Q times the rotation angular velocity.

In some embodiments of the present application, the first determining unit 22 is further configured to use the first angle parameter value of the predicted node as the second angle parameter value when the predicted node index value indicates that the predicted node is not a preset node.

In some embodiments of the present application, the first determination unit 22 is further configured to determine, based on the first decoded node, a second decoded node in a reference frame where the predicted node represented by the predicted node index value is located; the fourth angle parameter value of the second decoded node is less than or equal to and closest to the third angle parameter value of the first decoded node, and the second decoded node and the first decoded node have the same radar index; based on the second decoded node, determine the predicted node, the first angle parameter value of the predicted node is greater than the fourth angle parameter value of the second decoded node, and the predicted node and the second decoded node have the same radar index.

In some embodiments of the present application, the first determination unit 22 is further configured to use the fourth angle parameter value corresponding to the second decoded node as the first angle parameter value of the predicted node; or, in the reference frame where the predicted node is located, based on the second decoded node and the predicted node index value, determine at least one next decoded node, the at least one next decoded node including the predicted node; the next angle parameter value of the next decoded node is greater than and closest to the previous angle parameter value of its previous decoded node; the at least one next decoded node has the same radar index as the second decoded node.

In some embodiments of the present application, the first determination unit 22 is further configured to determine, based on the first decoded node, a second decoded node in a reference frame where the predicted node represented by the predicted node index value is located; the fourth angle parameter value of the second decoded node is less than or equal to and closest to the third angle parameter value of the first decoded node, and the second decoded node has the same radar index as the first decoded node; the fourth angle parameter value corresponding to the second decoded node is used as the first angle parameter value of the predicted node; or, in the decoded nodes after the second decoded node, the predicted node is determined according to the order of the prediction tree.

In some embodiments of the present application, the first determination unit 22 is further configured to determine the depth information of the predicted node, the radar index value of the predicted node, and the first angle parameter value as the geometric prediction value of the node to be decoded; or, to determine the depth information of the predicted node, the radar index value of the predicted node, and the second angle parameter value as the geometric prediction value of the node to be decoded.

In some embodiments of the present application, the first determination unit 22 is further configured to parse the bitstream to determine the geometric residual information and quantization parameters of the node to be decoded; based on the quantization parameters, perform inverse quantization processing on the geometric residual information to determine the geometric prediction residual; based on the geometric prediction residual and the geometric prediction value, determine the reconstructed geometric parameters of the node to be decoded.

In some embodiments of the present application, the first determination unit 22 is further configured to determine the context model of the node to be decoded according to the predicted node index value; and use the context model to decode the geometric residual information of the node to be decoded to obtain the geometric residual information.

In some embodiments of the present application, the first determination unit 22 is further configured to parse the code stream to determine first identification information; when the first identification information indicates that the node to be decoded uses an inter-frame prediction mode, execute the step of determining a predicted node based on the node index value and the first decoded node.

In some embodiments of the present application, the first determination unit 22 is further configured to, if the first identification information is a first value, determine that the first identification information indicates that the node to be decoded does not use the inter-frame prediction mode; if the first identification information is a second value, determine that the first identification information indicates that the node to be decoded uses the inter-frame prediction mode.

In some embodiments of the present application, the first determining unit 22 is further configured to parse the bitstream to determine the second identification information; when the second identification information indicates that the node to be decoded enables the local motion processing mode, the first decoded node is executed based on the first decoded bitstream. The code node performs local motion processing on the first angle parameter value of the prediction node to determine the second angle parameter value of the prediction node.

In some embodiments of the present application, the first determination unit 22 is further configured to, if the second identification information is a first value, determine that the second identification information indicates that the local motion processing mode is not enabled for the node to be decoded; if the second identification information is a second value, determine that the second identification information indicates that the local motion processing mode is enabled for the node to be decoded.

In some embodiments of the present application, the first determination unit 22 is further configured to determine a previous decoded node of the node to be decoded based on a decoding order of the prediction tree, and use the previous decoded node as the first decoded node.

It is understandable that in the embodiments of the present application, a "unit" may be a part of a circuit, a part of a processor, a part of a program or software, etc., and of course, it may be a module, or it may be non-modular. Moreover, the components in the present embodiment may be integrated into a processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of a software functional module.

If the integrated unit is implemented in the form of a software function module and is not sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this embodiment is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) or a processor to perform all or part of the steps of the method described in this embodiment. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc., various media that can store program codes.

Therefore, an embodiment of the present application provides a computer-readable storage medium, which is applied to the decoder 20. The computer-readable storage medium stores a computer program, and when the computer program is executed by the first processor, the method described in any one of the above embodiments is implemented.

Based on the composition of the above-mentioned decoder 20 and the computer-readable storage medium, refer to Figure 26, which shows a specific hardware structure diagram of the decoder 20 provided in an embodiment of the present application. As shown in Figure 26, the decoder 20 may include: a first communication interface 24, a first memory 25 and a first processor 26; each component is coupled together through a first bus system 27. It can be understood that the first bus system 27 is used to achieve connection and communication between these components. In addition to the data bus, the first bus system 27 also includes a power bus, a control bus and a status signal bus. However, for the sake of clarity, various buses are marked as the first bus system 27 in Figure 26. Among them,

The first communication interface 24 is used for receiving and sending signals during the process of sending and receiving information with other external network elements;

A first memory 25, for storing a computer program that can be run on the first processor 26;

The first processor 26 is configured to execute, when running the computer program:

Parse the bitstream and determine the predicted node index value corresponding to the node to be decoded;

Determine a first decoded node before the node to be decoded in the current frame;

Determine a prediction node according to the prediction node index value and the first decoded node;

Based on the first decoded node, performing local motion processing on the first angle parameter value of the prediction node to determine the second angle parameter value of the prediction node;

Determining a geometric parameter of the prediction node based on the first angle parameter value or the second angle parameter value;

Based on the geometric parameters, a geometric prediction value of the node to be decoded is determined.

It can be understood that the first memory 25 in the embodiment of the present application can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate synchronous DRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), and direct RAM bus RAM (DRRAM). The first memory 25 of the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

The first processor 26 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by a hardware integrated logic circuit or software instructions in the first processor 26. The above-mentioned first processor 26 can be a general-purpose processor, a digital signal processor (Digital Signal Processor, DSP), an application-specific integrated circuit (Application Specific Integrated Circuit, ASIC), a field programmable gate array (Field Programmable Gate Array, FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The present application can be implemented or executed The methods, steps and logic block diagrams disclosed in the examples. The general processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in the embodiments of the present application can be directly embodied as a hardware decoding processor for execution, or a combination of hardware and software modules in the decoding processor for execution. The software module can be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in the first memory 25, and the first processor 26 reads the information in the first memory 25, and completes the steps of the above method in combination with its hardware.

It is understood that the embodiments described in this application can be implemented in hardware, software, firmware, middleware, microcode or a combination thereof. For hardware implementation, the processing unit can be implemented in one or more application specific integrated circuits (Application Specific Integrated Circuits, ASIC), digital signal processors (Digital Signal Processing, DSP), digital signal processing devices (DSP Device, DSPD), programmable logic devices (Programmable Logic Device, PLD), field programmable gate arrays (Field-Programmable Gate Array, FPGA), general processors, controllers, microcontrollers, microprocessors, other electronic units for performing the functions described in this application or a combination thereof. For software implementation, the technology described in this application can be implemented by a module (such as a process, function, etc.) that performs the functions described in this application. The software code can be stored in a memory and executed by a processor. The memory can be implemented in the processor or outside the processor.

Optionally, as another embodiment, the first processor 26 is further configured to execute any one of the methods described in the foregoing embodiments when running the computer program.

The present embodiment provides a decoder in which the prediction nodes used for inter-frame prediction are mainly optimized. Specifically, local motion processing is performed on the angle parameter values of the prediction nodes, so that the inter-frame prediction can better predict the decoding nodes, thereby improving the accuracy of the inter-frame prediction, improving the encoding efficiency of the geometric information, and further improving the encoding and decoding performance of the point cloud.

In another embodiment of the present application, based on the same inventive concept as the above-mentioned embodiment, see FIG27 , which shows a schematic diagram of the composition structure of an encoder provided by an embodiment of the present application. As shown in FIG27 , the encoder 30 may include: a second determination unit 31, a second local motion processing unit 32 and a prediction unit 33; wherein,

The second determining unit 31 is configured to determine a first coded node preceding the node to be coded in the current frame; and determine a first candidate node having at least one geometric parameter identical to the first coded node in the reference frame, and determine at least one second candidate node in the reference frame according to the first candidate node;

The second local motion processing unit 32 is configured to perform local motion processing on the angle parameter value of at least one candidate node among the at least one second candidate node to obtain the updated at least one second candidate node;

The prediction unit 33 is configured to determine a geometric prediction value of the node to be encoded based on the first candidate node and at least one updated second candidate node.

In some embodiments of the present application, the fourth angle parameter value of the first candidate node is less than or equal to and closest to the third angle parameter value of the first encoded node.

In some embodiments of the present application, the second local motion processing unit 32 is further configured to determine the local motion information of each third candidate node based on the fourth angle parameter value of the first candidate node and the fifth angle parameter value of at least one third candidate node in the at least one second candidate node that matches the preset node; based on the local motion information, update the fifth angle parameter value of the corresponding third candidate node to determine the updated fifth angle parameter value of the at least one third candidate node, thereby determining the updated at least one third candidate node; and use the updated at least one third candidate node and the candidate nodes in the at least one second candidate node except the at least one third candidate node as the updated at least one second candidate node.

In some embodiments of the present application, the reference frame includes: a first reference frame and a second reference frame; the first reference frame is at least one frame obtained by performing global motion on the second reference frame; the second reference frame is an encoded frame of the previous K frames of the current frame, where K is an integer greater than 0.

In some embodiments of the present application, the preset node is at least one candidate node in the first reference frame except the first candidate node.

In some embodiments of the present application, the second local motion processing unit 32 is further configured to determine at least one third candidate node that matches the preset node from the at least one second candidate node; and determine the difference between the fourth angle parameter value of the first candidate node and the fifth angle parameter value of each of the third candidate nodes as the local motion information of each of the third candidate nodes.

In some embodiments of the present application, the second local motion processing unit 32 is also configured to determine the rotation angular velocity of the laser radar corresponding to the node to be encoded; based on the local motion information, the third angle parameter value and the rotation angular velocity of each third candidate node, determine the updated fifth angle parameter value of at least one third candidate node.

In some embodiments of the present application, the second local motion processing unit 32 is further configured to determine the first intermediate value of each third candidate node based on the ratio of the local motion information of each third candidate node to the rotation angular velocity; perform rounding operation on the first intermediate value of each third candidate node to obtain the second intermediate value of each third candidate node; multiply the second intermediate value of each third candidate node by the rotation angular velocity to obtain the third intermediate value of each third candidate node; add the third intermediate value of each third candidate node to the third angle parameter value respectively to obtain the updated fifth angle parameter value of each third candidate node.

In some embodiments of the present application, the second local motion processing unit 32 is also configured to update the fifth angle parameter value of any third candidate node based on the local motion information of any third candidate node, and determine the updated fifth angle parameter value of any third candidate node if the local motion information of any third candidate node is greater than or equal to a first preset threshold, or the difference value is less than or equal to a second preset threshold; the first preset threshold is greater than the second preset threshold.

In some embodiments of the present application, the second local motion processing unit 32 is also configured to not update the fifth angle parameter value of any third candidate node if the local motion information of any third candidate node is less than a first preset threshold and the local motion information is greater than a second preset threshold; the first preset threshold is greater than the second preset threshold.

In some embodiments of the present application, the first preset threshold is Q times the rotation angular velocity, where Q is a positive number; and the second preset threshold is negative Q times the rotation angular velocity.

In some embodiments of the present application, the first candidate node includes a first reference node and a second reference node; the second candidate node includes a third reference node and a fourth reference node; the first reference node and the third reference node belong to a first reference frame; the second reference node and the fourth reference node belong to a second reference frame.

In some embodiments of the present application, the second determination unit 31 is further configured to determine the first reference node having the same radar index as the first encoded node in the second reference frame; determine at least one third reference node in the first reference frame based on the first reference node; determine the second reference node having the same radar index as the first encoded node in the first reference frame; and determine at least one fourth reference node in the second reference frame based on the second reference candidate node.

In some embodiments of the present application, the fourth angle parameter value of the first reference node is less than or equal to and closest to the third angle parameter value of the first encoded node; the sixth angle parameter value of the at least one third reference node is greater than the fourth angle parameter value of the first reference node, and the at least one third reference node has the same radar index as the first reference node; the fourth angle parameter value of the second reference node is less than or equal to and closest to the third angle parameter value of the first encoded node; the seventh angle parameter value of the at least one fourth reference node is greater than the fourth angle parameter value of the second reference node, and the at least one fourth reference node has the same radar index as the second reference node.

In some embodiments of the present application, the second determination unit 31 is further configured to determine, in the first reference frame, at least one third reference node that is sequentially encoded after the first reference node according to the order of the prediction tree.

In some embodiments of the present application, the second determination unit 31 is further configured to determine, in the second reference frame, at least one fourth reference node that is sequentially encoded after the second reference node according to the order of the prediction tree.

In some embodiments of the present application, the second local motion processing unit 32 is further configured to determine the local motion information of each third candidate node based on the fourth angle parameter value of the first reference node and the fifth angle parameter value of at least one third candidate node that matches the preset node in the at least one third reference node; based on the local motion information, update the fifth angle parameter value of the corresponding third candidate node to determine the updated fifth angle parameter value of the at least one third candidate node, thereby determining the updated at least one third candidate node; use the updated at least one third candidate node and the candidate nodes in the at least one third reference node except the at least one third candidate node as the updated at least one third reference node; use the updated at least one third reference node and the at least one fourth reference node as the updated at least one second candidate node.

In some embodiments of the present application, the at least one third reference node, the updated at least one fourth reference node, the second reference node and the first reference node have a preset order.

In some embodiments of the present application, the prediction unit 33 is further configured to perform cost calculations on the first candidate node and each of the updated second candidate nodes, respectively, to obtain multiple rate-distortion cost results; determine the candidate node corresponding to the minimum rate-distortion cost among the multiple rate-distortion cost results as the prediction node; and determine the geometric prediction value of the node to be encoded based on the prediction node.

In some embodiments of the present application, the second determination unit 31 is further configured to determine a predicted node index value corresponding to the node to be encoded in a preset order; encode the predicted node index value, and write the obtained encoded bits into a bitstream.

In some embodiments of the present application, the second determination unit 31 is further configured to determine the geometric residual information of the node to be encoded based on the geometric prediction value of the node to be encoded; encode the geometric residual information of the node to be encoded, and write the obtained encoded bits into the bit stream.

In some embodiments of the present application, the second determination unit 31 is further configured to determine the initial residual value of the node to be encoded based on the geometric prediction value of the node to be encoded; and quantize the initial residual value of the node to be encoded according to a quantization parameter to obtain the geometric residual information of the node to be encoded.

In some embodiments of the present application, the prediction unit 33 is further configured to determine the original value of the node to be encoded; and determine the initial residual value of the node to be encoded by performing a subtraction operation between the original value of the node to be encoded and the geometric prediction value of the node to be encoded.

In some embodiments of the present application, the prediction unit 33 is further configured to encode the quantization parameter and write the obtained encoded bits into a bit stream.

In some embodiments of the present application, the second determination unit 31 is also configured to determine a prediction mode of the node to be encoded, and generate first identification information based on the prediction mode; the first identification information indicates whether the node to be encoded uses an inter-frame prediction mode; when the prediction mode is an inter-frame prediction mode, the step of determining the first encoded node in the previous one of the node to be encoded in the current frame is performed.

In some embodiments of the present application, the second determination unit 31 is further configured to determine that the value of the first identification information is a first value if the first identification information indicates that the node to be encoded does not use the inter-frame prediction mode; if the first identification information indicates that the node to be encoded uses the inter-frame prediction mode, determine that the value of the first identification information is a second value.

In some embodiments of the present application, the second determining unit 31 is further configured to encode the first identification information and write the obtained encoded bits into a bit stream.

In some embodiments of the present application, the second determination unit 31 is further configured to determine whether the local motion processing mode is enabled and generate second identification information; the second identification information indicates whether the local motion processing mode is enabled for the node to be encoded; when it is determined that the local motion processing mode is enabled for the node to be encoded, the step of determining the first encoded node in the previous one of the node to be encoded in the current frame is performed.

In some embodiments of the present application, the second determination unit 31 is further configured to determine that the value of the second identification information is a first value if the second identification information indicates that the node to be encoded does not enable the local motion processing mode; if the second identification information indicates that the node to be encoded enables the local motion processing mode, determine that the value of the second identification information is a second value.

In some embodiments of the present application, the second determining unit 31 is further configured to encode the second identification information and write the obtained encoded bits into a bit stream.

In some embodiments of the present application, the second determination unit 31 is further configured to determine a previous encoded node of the node to be encoded based on the encoding order of the prediction tree, and use the previous encoded node as the first encoded node.

It can be understood that in this embodiment, a "unit" can be a part of a circuit, a part of a processor, a part of a program or software, etc., and of course it can also be a module, or it can be non-modular. Moreover, the components in this embodiment can be integrated into a processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of a software functional module.

If the integrated unit is implemented in the form of a software function module and is not sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, this embodiment provides a computer-readable storage medium, which is applied to the encoder 30, and the computer-readable storage medium stores a computer program. When the computer program is executed by the second processor, the method described in any one of the above embodiments is implemented.

Based on the composition of the above-mentioned encoder 30 and the computer-readable storage medium, refer to Figure 28, which shows a specific hardware structure diagram of the encoder 30 provided in an embodiment of the present application. As shown in Figure 28, the encoder 30 may include: a second communication interface 34, a second memory 35 and a second processor 36; each component is coupled together through a second bus system 37. It can be understood that the second bus system 37 is used to realize the connection and communication between these components. In addition to the data bus, the second bus system 37 also includes a power bus, a control bus and a status signal bus. However, for the sake of clarity, various buses are marked as the second bus system 37 in Figure 28. Among them,

The second communication interface 34 is used for receiving and sending signals during the process of sending and receiving information with other external network elements;

A second memory 35, used for storing a computer program that can be run on the second processor 3003;

The second processor 36 is configured to execute, when running the computer program:

Determine a first encoded node preceding a node to be encoded in a current frame;

Determine a first candidate node having at least one geometric parameter identical to that of the first encoded node in a reference frame, and determine at least one second candidate node in the reference frame based on the first candidate node;

Performing local motion processing on the angle parameter value of at least one candidate node among the at least one second candidate node to obtain at least one updated second candidate node;

Based on the first candidate node and at least one updated second candidate node, a geometric prediction value of the node to be encoded is determined.

Optionally, as another embodiment, the second processor 36 is further configured to execute the aforementioned implementation when running the computer program. The method described in any one of the examples.

It can be understood that the hardware functions of the second memory 35 and the first memory 25 are similar, and the hardware functions of the second processor 36 and the first processor 26 are similar; they will not be described in detail here.

The present embodiment provides an encoder, in which the candidate nodes for inter-frame prediction are mainly optimized. Specifically, local motion processing is performed on the angle parameter values of the candidate nodes, so that the inter-frame prediction can better predict the coding nodes, thereby improving the accuracy of the inter-frame prediction, improving the coding efficiency of the geometric information, and further improving the encoding and decoding performance of the point cloud.

In yet another embodiment of the present application, referring to FIG29 , a schematic diagram of the composition structure of a coding and decoding system provided in an embodiment of the present application is shown. As shown in FIG29 , the coding and decoding system 40 may include an encoder 30 and a decoder 20 .

In the embodiment of the present application, the encoder 30 may be the encoder described in any one of the aforementioned embodiments, and the decoder 20 may be the decoder described in any one of the aforementioned embodiments.

It should be noted that, in this application, the terms "include", "comprises" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

The methods disclosed in several method embodiments provided in this application can be arbitrarily combined without conflict to obtain new method embodiments.

The features disclosed in several product embodiments provided in this application can be arbitrarily combined without conflict to obtain new product embodiments.

The features disclosed in several method or device embodiments provided in this application can be arbitrarily combined without conflict to obtain new method embodiments or device embodiments.

The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Industrial Applicability

In an embodiment of the present application, at the decoding end, the code stream is first parsed to determine the predicted node index value corresponding to the node to be decoded; then, the first decoded node before the node to be decoded in the current frame is determined; then, the predicted node is determined based on the predicted node index value and the first decoded node; then, based on the first decoded node, the first angle parameter value of the predicted node is subjected to local motion processing to determine the second angle parameter value of the predicted node; finally, based on the first angle parameter value or the second angle parameter value, the geometric parameter of the predicted node is determined; based on the geometric parameter, the geometric prediction value of the node to be decoded is determined. At the encoding end, the first encoded node before the node to be encoded in the current frame is first determined; then, a first candidate node having at least one geometric parameter identical to the first encoded node in the reference frame is determined, and at least one second candidate node is determined in the reference frame based on the first candidate node; then, the angle parameter value of at least one candidate node in the at least one second candidate node is subjected to local motion processing to obtain at least one updated second candidate node; finally, based on the first candidate node and the at least one updated second candidate node, the geometric prediction value of the node to be encoded is determined. In this way, the technical solution of the present application is mainly aimed at optimizing the candidate nodes used for inter-frame prediction. Compared with the related technologies, local motion processing is performed on the angle parameter values of the candidate nodes, so that the inter-frame prediction can better predict the nodes to be decoded, thereby improving the accuracy of the inter-frame prediction, improving the encoding and decoding efficiency of the geometric information, and further improving the encoding and decoding performance of the point cloud.

Claims (58)

A decoding method, applied to a decoder, comprising: Parse the bitstream and determine the predicted node index value corresponding to the node to be decoded; Determine a first decoded node before the node to be decoded in the current frame; Determine a prediction node according to the prediction node index value and the first decoded node; Based on the first decoded node, performing local motion processing on the first angle parameter value of the prediction node to determine the second angle parameter value of the prediction node; Determining a geometric parameter of the prediction node based on the first angle parameter value or the second angle parameter value; Based on the geometric parameters, a geometric prediction value of the node to be decoded is determined. The method according to claim 1, wherein the performing local motion processing on the first angle parameter value of the predicted node based on the first decoded node to determine the second angle parameter value of the predicted node comprises: In the case where the predicted node index value represents that the predicted node is a preset node, local motion information is determined based on the fourth angle parameter value of the second decoded node and the first angle parameter value of the predicted node; the fourth angle parameter value of the second decoded node is less than or equal to and closest to the third angle parameter value of the first decoded node; the second decoded node is determined based on the first decoded node in the reference frame where the predicted node is located; Based on the local motion information, the second angle parameter value of the prediction node is determined. The method according to claim 2, wherein The reference frame where the prediction node is located includes: a first reference frame and a second reference frame; The first reference frame is at least one frame obtained by performing global motion on the second reference frame; The second reference frame is a decoded frame that is K frames before the current frame, where K is an integer greater than 0. The method according to claim 2 or 3, wherein: The preset node is at least one decoded node in the first reference frame except the second decoded node. The method according to any one of claims 2 to 4, wherein the determining the local motion information based on the acquired fourth angle parameter value of the second decoded node and the first angle parameter value of the predicted node comprises: A difference value between the fourth angle parameter value of the second decoded node and the first angle parameter value of the predicted node is determined as the local motion information. The method according to any one of claims 2 to 5, wherein determining the second angle parameter value of the prediction node based on the local motion information comprises: Determine the rotation angular velocity of the laser radar corresponding to the node to be decoded; The second angle parameter value is determined based on the local motion information, the third angle parameter value and the rotation angular velocity. The method according to claim 6, wherein the determining the second angle parameter value based on the local motion information, the third angle parameter value and the rotation angular velocity comprises: Determining a first intermediate value based on a ratio of the local motion information to the rotation angular velocity; performing a rounding operation on the first intermediate value to obtain a second intermediate value; multiplying the second intermediate value by the rotation angular velocity to obtain a third intermediate value; The third intermediate value and the third angle parameter value are added to obtain the second angle parameter value. The method according to any one of claims 2 to 7, wherein determining the second angle parameter value of the prediction node based on the local motion information comprises: If the local motion information is greater than or equal to a first preset threshold, or the local motion information is less than or equal to a second preset threshold, the second angle parameter value of the prediction node is determined based on the local motion information; the first preset threshold is greater than the second preset threshold. The method according to any one of claims 2 to 7, wherein the method further comprises: If the local motion information is less than a first preset threshold and the local motion information is greater than a second preset threshold, the first angle parameter value is determined as the second angle parameter value; and the first preset threshold is greater than the second preset threshold. The method according to claim 8 or 9, wherein The first preset threshold is Q times the rotation angular velocity, where Q is a positive number; The second preset threshold is negative Q times the rotation angular velocity. The method according to claim 1, wherein the method further comprises: The predicted node index value represents that when the predicted node is not a preset node, the first angle parameter value of the predicted node is used as the second angle parameter value. The method according to any one of claims 1 to 11, wherein determining the predicted node according to the predicted node index value and the first decoded node comprises: According to the first decoded node, in a reference frame where the predicted node represented by the predicted node index value is located, a second decoded node is determined; the fourth angle parameter value of the second decoded node is less than or equal to and closest to the third angle parameter value of the first decoded node, and the second decoded node has the same radar index as the first decoded node; Based on the second decoded node, the predicted node is determined, a first angle parameter value of the predicted node is greater than a fourth angle parameter value of the second decoded node, and the predicted node has the same radar index as the second decoded node. The method according to claim 12, wherein the determining the predicted node based on the second decoded node comprises: using the fourth angle parameter value corresponding to the second decoded node as the first angle parameter value of the predicted node; or, In the reference frame where the predicted node is located, at least one next decoded node is determined based on the second decoded node and the predicted node index value, wherein the at least one next decoded node includes the predicted node; a next angle parameter value of the next decoded node is greater than and closest to a previous angle parameter value of its previous decoded node; and the at least one next decoded node has the same radar index as the second decoded node. The method according to any one of claims 1 to 11, wherein determining the predicted node according to the predicted node index value and the first decoded node comprises: According to the first decoded node, in a reference frame where the predicted node represented by the predicted node index value is located, a second decoded node is determined; the fourth angle parameter value of the second decoded node is less than or equal to and closest to the third angle parameter value of the first decoded node, and the second decoded node has the same radar index as the first decoded node; using the fourth angle parameter value corresponding to the second decoded node as the first angle parameter value of the predicted node; or, The predicted node is determined in the decoded nodes after the second decoded node according to the order of the prediction tree. The method according to any one of claims 1 to 14, wherein determining the geometric parameter of the prediction node based on the first angle parameter value or the second angle parameter value comprises: Determine the depth information of the prediction node, the radar index value of the prediction node, and the first angle parameter value as the geometric parameter of the prediction node; or, The depth information of the prediction node, the radar index value of the prediction node, and the second angle parameter value are determined as the geometric parameters of the prediction node. The method according to claim 15, wherein the method further comprises: Parsing the bitstream to determine the geometric residual information and quantization parameter of the node to be decoded; Based on the quantization parameter, inverse quantization is performed on the geometric residual information to determine a geometric prediction residual; Based on the geometric prediction residual and the geometric prediction value, a reconstructed geometric parameter of the node to be decoded is determined. The method according to claim 16, wherein determining the geometric residual information of the node to be decoded comprises: Determining a context model of the node to be decoded according to the predicted node index value; The context model is used to decode the geometric residual information of the node to be decoded to obtain the geometric residual information. The method according to any one of claims 1 to 17, wherein: Parsing the code stream to determine the first identification information; When the first identification information indicates that the node to be decoded uses an inter-frame prediction mode, a step of determining a prediction node according to the node index value and the first decoded node is performed. The method according to claim 18, wherein If the first identification information is a first value, determining that the first identification information indicates that the node to be decoded does not use an inter-frame prediction mode; If the first identification information is the second value, it is determined that the first identification information indicates that the node to be decoded uses an inter-frame prediction mode. The method according to any one of claims 1 to 19, wherein the method further comprises: Parsing the code stream to determine the second identification information; When the second identification information indicates that the node to be decoded enables local motion processing, a step is performed to perform local motion processing on the first angle parameter value of the predicted node based on the first decoded node to determine the second angle parameter value of the predicted node. The method according to claim 20, wherein the method further comprises: If the second identification information is the first value, determining that the second identification information indicates that the node to be decoded does not enable a local motion processing mode; If the second identification information is a second value, it is determined that the second identification information indicates that the to-be-decoded node enables a local motion processing mode. The method according to any one of claims 1 to 21, wherein determining a first decoded node before the node to be decoded in the current frame comprises: Based on the decoding order of the prediction tree, a previous decoded node of the node to be decoded is determined, and the previous decoded node is used as the first decoded node. A coding method, applied to an encoder, comprising: Determine a first encoded node preceding a node to be encoded in a current frame; Determine a first candidate node having at least one geometric parameter identical to that of the first encoded node in a reference frame, and determine at least one second candidate node in the reference frame based on the first candidate node; Performing local motion processing on the angle parameter value of at least one candidate node among the at least one second candidate node to obtain at least one updated second candidate node; Based on the first candidate node and at least one updated second candidate node, a geometric prediction value of the node to be encoded is determined. The method according to claim 23, wherein the fourth angle parameter value of the first candidate node is less than or equal to and closest to the third angle parameter value of the first encoded node. The method according to claim 23, wherein the performing local motion processing on the angle parameter value of at least one of the at least one second candidate node to obtain the updated at least one second candidate node comprises: Determine local motion information of each third candidate node based on the fourth angle parameter value of the first candidate node and the fifth angle parameter value of at least one third candidate node among the at least one second candidate node that matches the preset node; Based on the local motion information, updating the fifth angle parameter value of the corresponding third candidate node, determining the updated fifth angle parameter value of the at least one third candidate node, thereby determining the updated at least one third candidate node; The at least one updated third candidate node and the at least one second candidate node, except the at least one third candidate node, are used as the at least one updated second candidate node. The method according to any one of claims 23 to 25, wherein: The reference frame includes: a first reference frame and a second reference frame; The first reference frame is at least one frame obtained by performing global motion on the second reference frame; The second reference frame is an encoded frame that is K frames before the current frame, where K is an integer greater than 0. The method according to claim 25, wherein The preset node is at least one candidate node in the first reference frame except the first candidate node. The method according to claim 25 or 27, wherein the determining the local motion information of each third candidate node based on the fourth angle parameter value of the first candidate node and the fifth angle parameter value of at least one third candidate node matching the preset node among the at least one second candidate node comprises: Determine, from the at least one second candidate node, at least one third candidate node that matches the preset node; The difference between the fourth angle parameter value of the first candidate node and the fifth angle parameter value of each of the third candidate nodes is respectively determined as the local motion information of each of the third candidate nodes. The method according to any one of claims 25, 27 or 28, wherein the updating of the fifth angle parameter value of the corresponding third candidate node based on the local motion information to determine the updated fifth angle parameter value of the at least one third candidate node comprises: Determine the rotation angular velocity of the laser radar corresponding to the node to be encoded; The updated fifth angle parameter value of the at least one third candidate node is determined based on the local motion information, the third angle parameter value and the rotation angular velocity of each third candidate node. The method according to claim 29, wherein the determining the updated fifth angle parameter value of the at least one third candidate node based on the local motion information, the third angle parameter value and the rotation angular velocity of each third candidate node comprises: Determine a first intermediate value of each third candidate node based on a ratio of the local motion information of each third candidate node to the rotation angular velocity; Performing a rounding operation on the first intermediate value of each third candidate node to obtain a second intermediate value of each third candidate node; The second intermediate value of each third candidate node is multiplied by the rotation angular velocity to obtain the third value of each third candidate node. median value; The third intermediate value of each third candidate node is added to the third angle parameter value to obtain the updated fifth angle parameter value of each third candidate node. The method according to claim 29, wherein the determining the updated fifth angle parameter value of the at least one third candidate node based on the local motion information, the third angle parameter value and the rotation angular velocity of each third candidate node comprises: If the local motion information of any third candidate node is greater than or equal to a first preset threshold, or the local motion information is less than or equal to a second preset threshold, the fifth angle parameter value of any third candidate node is updated based on the local motion information of any third candidate node to determine the updated fifth angle parameter value of any third candidate node; the first preset threshold is greater than the second preset threshold. The method according to claim 29, wherein the method further comprises: If the local motion information of any third candidate node is less than the first preset threshold and the local motion information is greater than the second preset threshold, the fifth angle parameter value of any third candidate node is not updated; the first preset threshold is greater than the second preset threshold. The method according to claim 31 or 32, wherein The first preset threshold is Q times the rotation angular velocity, where Q is a positive number; The second preset threshold is negative Q times the rotation angular velocity. The method according to any one of claims 23 to 33, wherein the first candidate node includes a first reference node and a second reference node; the second candidate node includes a third reference node and a fourth reference node; the first reference node and the third reference node belong to a first reference frame; the second reference node and the fourth reference node belong to a second reference frame; The determining at least one second candidate node in the reference frame according to the first candidate node comprises: determining the first reference node having the same radar index as the first encoded node in the first reference frame; determining at least one third reference node in the first reference frame according to the first reference node; determining the second reference node having the same radar index as the first encoded node in the second reference frame; At least one fourth reference node is determined in the second reference frame according to the second reference candidate node. The method according to claim 34, wherein The fourth angle parameter value of the first reference node is less than or equal to and closest to the third angle parameter value of the first encoded node; The sixth angle parameter value of the at least one third reference node is greater than the fourth angle parameter value of the first reference node, and the at least one third reference node has the same radar index as the first reference node; The fourth angle parameter value of the second reference node is less than or equal to and closest to the third angle parameter value of the first encoded node; The seventh angle parameter value of the at least one fourth reference node is greater than the fourth angle parameter value of the second reference node, and the at least one fourth reference node has the same radar index as the second reference node. The method according to claim 34, wherein determining at least one third reference node in the first reference frame based on the first reference node comprises: In the first reference frame, at least one third reference node that is sequentially encoded after the first reference node is determined according to the order of the prediction tree. The method according to claim 34 or 36, wherein the determining at least one fourth reference node in the second reference frame according to the second reference candidate node comprises: In the second reference frame, at least one fourth reference node that is sequentially encoded after the second reference node is determined according to the order of the prediction tree. The method according to any one of claims 34 to 37, wherein the performing local motion processing on the angle parameter value of at least one candidate node among the at least one second candidate node to obtain the updated at least one second candidate node comprises: Determine local motion information of each third candidate node based on the fourth angle parameter value of the first reference node and the fifth angle parameter value of at least one third candidate node among the at least one third reference node that matches the preset node; Based on the local motion information, updating the fifth angle parameter value of the corresponding third candidate node, determining the updated fifth angle parameter value of the at least one third candidate node, thereby determining the updated at least one third candidate node; using the updated at least one third candidate node and the candidate node other than the at least one third candidate node among the at least one third reference node as the updated at least one third reference node; The updated at least one third reference node and the at least one fourth reference node are used as the updated at least one second candidate node. Select a node. The method according to claim 38, wherein The at least one third reference node, the updated at least one fourth reference node, the second reference node, and the first reference node have a preset order. The method according to claim 23, wherein the determining the geometric prediction value of the node to be encoded based on the first candidate node and the updated at least one second candidate node comprises: Performing cost calculations on the first candidate node and each of the updated second candidate nodes respectively to obtain multiple rate-distortion cost results; Determine a candidate node corresponding to a minimum rate-distortion cost among the multiple rate-distortion cost results as a prediction node; Based on the prediction node, a geometric prediction value of the node to be encoded is determined. The method according to claim 23, wherein the method further comprises: Determining a predicted node index value corresponding to the node to be encoded in a preset order; The predicted node index value is encoded, and the obtained encoding bits are written into a bit stream. The method according to claim 23, wherein the method further comprises: Determining geometric residual information of the node to be encoded according to the geometric prediction value of the node to be encoded; The geometric residual information of the node to be encoded is encoded, and the obtained encoding bits are written into a bit stream. The method according to claim 42, wherein determining the geometric residual information of the node to be encoded according to the geometric prediction value of the node to be encoded comprises: Determining an initial residual value of the node to be encoded according to the geometric prediction value of the node to be encoded; The initial residual value of the node to be encoded is quantized according to the quantization parameter to obtain the geometric residual information of the node to be encoded. The method according to claim 43, wherein determining the initial residual value of the node to be encoded according to the geometric prediction value of the node to be encoded comprises: Determining the original value of the node to be encoded; An initial residual value of the node to be encoded is determined by performing a subtraction operation on the original value of the node to be encoded and the geometric prediction value of the node to be encoded. The method according to claim 43, wherein the method further comprises: The quantization parameter is encoded, and the obtained encoded bits are written into a bit stream. The method according to any one of claims 23 to 45, wherein the method further comprises: Determine a prediction mode of a node to be encoded, and generate first identification information based on the prediction mode; the first identification information indicates whether the node to be encoded uses an inter-frame prediction mode; When the prediction mode is the inter-frame prediction mode, the step of determining the first encoded node before the node to be encoded in the current frame is performed. The method according to claim 46, wherein determining the prediction mode of the node to be encoded and generating the first identification information based on the prediction mode comprises: If the first identification information indicates that the node to be encoded does not use the inter-frame prediction mode, determining that the value of the first identification information is a first value; If the first identification information indicates that the node to be encoded uses the inter-frame prediction mode, the value of the first identification information is determined to be a second value. The method according to claim 46, wherein the method further comprises: The first identification information is encoded, and the obtained encoded bits are written into a bit stream. The method according to any one of claims 23 to 45, wherein the method further comprises: Determine whether to enable the local motion processing mode, and generate second identification information; the second identification information indicates whether the local motion processing mode is enabled for the node to be encoded; In the case where it is determined that the local motion processing mode is enabled for the node to be encoded, the step of determining the first encoded node before the node to be encoded in the current frame is performed. The method according to claim 49, wherein the determining whether to enable the local motion processing mode and generating the second identification information comprises: If the second identification information indicates that the node to be encoded does not enable the local motion processing mode, determining that the value of the second identification information is a first value; If the second identification information indicates that the node to be encoded enables the local motion processing mode, then determining the The value is the second value. The method according to claim 49, wherein the method further comprises: The second identification information is encoded, and the obtained encoded bits are written into a bit stream. The method according to any one of claims 23 to 51, wherein determining the first encoded node before the node to be encoded in the current frame comprises: Based on the coding order of the prediction tree, a previous coded node of the node to be coded is determined, and the previous coded node is used as the first coded node. A code stream, wherein the code stream is generated by bit encoding according to information to be encoded; wherein the information to be encoded includes at least one of the following: The geometric prediction residual value, quantization parameter, prediction node index value, first identification information and second identification information of the node to be encoded; The first identification information is used to indicate whether the node to be encoded uses an inter-frame prediction mode, and the second identification information is used to indicate whether the node to be encoded enables a local motion processing mode. A decoder, comprising a decoding unit, a first determining unit and a first local motion processing unit; wherein: The decoding unit is configured to parse the bitstream, determine the predicted node index value corresponding to the node to be decoded; and determine the first decoded node before the node to be decoded in the current frame; The first determining unit is configured to determine a prediction node according to the prediction node index value and the first decoded node; The first local motion processing unit is configured to perform local motion processing on the first angle parameter value of the prediction node based on the first decoded node to determine the second angle parameter value of the prediction node; The first determination unit is further configured to determine the geometric parameters of the predicted node based on the first angle parameter value or the second angle parameter value; and determine the geometric prediction value of the node to be decoded based on the geometric parameters. A decoder, comprising a first memory and a first processor; wherein: The first memory is configured to store a computer program that can be executed on the first processor; The first processor is configured to perform the method according to any one of claims 1 to 22 when running the computer program. An encoder comprises a second determination unit, a second local motion processing unit and a prediction unit; wherein, The second determination unit is configured to determine a first coded node preceding the node to be coded in the current frame; and determine a first candidate node having at least one geometric parameter identical to the first coded node in the reference frame, and determine at least one second candidate node in the reference frame according to the first candidate node; The second local motion processing unit is configured to perform local motion processing on the angle parameter value of at least one candidate node among the at least one second candidate node to obtain the updated at least one second candidate node; The prediction unit is configured to determine a geometric prediction value of the node to be encoded based on the first candidate node and at least one updated second candidate node. An encoder comprises a second memory and a second processor; wherein: The second memory is configured to store a computer program that can be executed on the second processor; The second processor is configured to perform the method according to any one of claims 23 to 52 when running the computer program. A computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a first processor, it implements the method as described in any one of claims 1 to 22, or when the computer program is executed by a second processor, it implements the method as described in any one of claims 23 to 52.