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WO2019062166A1 - 跨平台月基对地观测影像自动几何校正方法 - Google Patents

跨平台月基对地观测影像自动几何校正方法 Download PDF

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WO2019062166A1
WO2019062166A1 PCT/CN2018/088154 CN2018088154W WO2019062166A1 WO 2019062166 A1 WO2019062166 A1 WO 2019062166A1 CN 2018088154 W CN2018088154 W CN 2018088154W WO 2019062166 A1 WO2019062166 A1 WO 2019062166A1
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moon
image
observation
platform
point
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郭华东
张露
刘广
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Institute of Remote Sensing and Digital Earth of CAS
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Institute of Remote Sensing and Digital Earth of CAS
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Priority claimed from CN201710944206.3A external-priority patent/CN107462220B/zh
Priority claimed from CN201710974189.8A external-priority patent/CN107657597B/zh
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Publication of WO2019062166A1 publication Critical patent/WO2019062166A1/zh
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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/80—Geometric correction
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T3/00—Geometric image transformations in the plane of the image
    • G06T3/14—Transformations for image registration, e.g. adjusting or mapping for alignment of images
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/50—Image enhancement or restoration using two or more images, e.g. averaging or subtraction
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/30—Determination of transform parameters for the alignment of images, i.e. image registration
    • G06T7/33—Determination of transform parameters for the alignment of images, i.e. image registration using feature-based methods
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10032—Satellite or aerial image; Remote sensing
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30181—Earth observation

Definitions

  • the invention relates to the field of earth observation, and particularly relates to a method for automatically geometrically correcting a cross-platform moon-based observation image, in particular to an automatic geometric correction of a cross-platform moon-based observation image based on the projection of the moon point projection polar coordinates. method.
  • the research team headed by Academician Guo Huadong proposed a new idea of the moon-based platform for Earth observation.
  • the Moon is the only natural satellite of the Earth. It has the characteristics of integrity and stability in observing the Earth, and provides a more ideal observation platform for studying the macroscopic scientific phenomena of the Earth.
  • the monthly base-to-earth observation achieves the instantaneous acquisition of the hemispherical image, and the monthly base platform is obtained due to the influence of the ultra-long distance of 384,000 kilometers, special geometric observation conditions, the movement of the moon point, and the scale of the planet.
  • the difficulty of accurate geometric correction of ground observation data is manifested by the geometrical variation of different regions of the hemispherical image caused by the curvature of the earth, the problem of image center shift caused by the moon's lower point, the change of the observed area caused by the movement of the morning faint line, and the cause.
  • the number of control points caused by large areas of oceans, clouds, etc. is sparse and unevenly distributed.
  • Geometric correction is to map the coordinates of remote sensing images with the coordinates of corresponding ground points.
  • the traditional geometric correction methods are applicable to the geometric correction of local small area, and often ignore the influence of earth curvature on geometric distortion.
  • the geometric correction of remote sensing images has limitations. Therefore, it is very necessary and important to develop a geometric correction method suitable for the moon-based platform to observe the image of the moon-based platform.
  • the invention discloses a cross-platform monthly base-to-earth observation image automatic geometric correction method, which comprises the following steps: the step of acquiring the geometric parameters of the moon-based platform observation, and determining the geometric parameters of the moon-based ground observation by using the relationship between the sun and the moon;
  • the remote sensing image projection polar coordinate expression step using the monthly base-to-ground observation geometric parameter, the geocoded on-board remote sensing image is expressed as a projection polar coordinate form based on the moon point;
  • the monthly base platform image simulation step according to the month
  • the geometric accuracy requirements of the ground-based observation image of the base platform are converted into the moon-based platform simulation image by the interpolation method to form a base-base platform simulation image base map database; and the moon-based observation and simulation image matching
  • the observation image obtained by the moon-based platform is matched with the base-base platform simulation image base map of the corresponding observation time in the moon-base platform simulation image base map database, and the geometric correction of the moon-based observation image is completed.
  • the monthly base-to-ground observation geometric parameters include month-down point information and morning faint line information.
  • the step-by-step platform observation geometric parameter acquisition step specifically includes the following sub-steps: a sub-point information acquisition sub-step, according to the observation time (T 0 ) and the day The relationship between the month and the land, determine the geographic coordinates (L 0 , B 0 ) of the observation point, and the sub-step of the morning faint line information. According to the observation time and the relationship between the sun and the moon, determine the information of the morning faint line at the observation time, and obtain the platform of the moon base at that time. Effective range of observations and day and night range.
  • the step of expressing the polar coordinates of the on-board remote sensing image projection specifically includes the following sub-steps: a global elevation data acquisition sub-step, and acquiring a satellite load similar to the monthly base platform sensor type
  • the sensor data is spliced to form a global geocoded image to obtain global elevation data; the global elevation data acquisition substep of the observation area, and the effective observation range for the observation time (T 0 ) obtained according to the observation step of the geometric parameter acquisition of the monthly base platform,
  • T 0 effective observation range for the observation time obtained according to the observation step of the geometric parameter acquisition of the monthly base platform,
  • the spaceborne remote sensing image of the observation area and the global elevation data of the corresponding area are obtained; based on the polar coordinate expression substep of the month point, the spaceborne remote sensing image of the observation area is expressed as a projection polar coordinate form based on the moon point.
  • the polar coordinate expression sub-step based on the moon-down point includes the following sub-steps: expressing the geographical information of the on-board remote sensing image in a geodetic coordinate system (L, B) , H); converting the onboard remote sensing image expressed by the geodetic coordinate system (L, B, H) into a spatial rectangular coordinate system (X, Y, Z); and using the spatial rectangular coordinate system (X, The spaceborne remote sensing image expressed by Y, Z) is converted into an orthographic projection polar coordinate ( ⁇ , ⁇ ) based on the moon point, and the (X, Y, Z- ⁇ , ⁇ ) correspondence table of the image is saved;
  • (X 0 , Y 0 , Z 0 ) is the known coordinate point of the month
  • (X, Y, Z) is the coordinate value of any point on the ellipsoid
  • (X', Y', Z') is (X) , Y, Z) the coordinates on the projection surface S
  • (X' n , ' Y' n , Z' n ) is the coordinate value of the north pole point N on the projection surface S
  • ⁇ is (X, Y, Z)
  • ⁇ is the angle between (X, Y, Z) and (X' n , Y′ n , Z′ n ) in the S projection plane.
  • the month-based platform image simulation step specifically includes the following sub-steps: observing image geometric parameters according to the monthly base platform, and using the polar coordinates ( ⁇ , ⁇ )
  • the expressed on-board remote sensing image is interpolated to make it satisfy the uniform distribution of ⁇ , and the distribution of ⁇ is uniform, and it is consistent with the geometric scale of the observation image of the moon-based platform.
  • the simulation image of the moon-based platform is obtained, and the geometric information is ( ⁇ s , ⁇ s ); according to the geometric information ( ⁇ s , ⁇ s ) of the simulated image of the moon-based platform, using the (X, Y, Z- ⁇ , ⁇ ) correspondence table to clarify the simulated image of the moon-based platform
  • the geometric information ( ⁇ s , ⁇ s ) corresponds to (X s , Y s , Z s ); and the simulated image of the moon-based platform and the corresponding ( ⁇ s , ⁇ s -X s , Y s , Z s )
  • the table is stored in the base image of the base image platform.
  • the month-based platform observation and simulation image registration step specifically includes the following sub-steps: according to the observation time and the monthly period motion law, from the month base Extracting the corresponding base-base platform simulation image base map and ( ⁇ s , ⁇ s -X s , Y s , Z s ) table in the platform simulation image base map database; selecting the registration suitable for the image type of the moon-based platform observation
  • the moon-based platform observation image is registered to the moon-based platform simulation image basemap, and the geometric correction of the observation image of the moon-based platform is completed.
  • the registration method is a scale-invariant feature conversion method.
  • the geodetic coordinate system (L, B, H) and the spatial rectangular coordinate system (X, Y) , Z) conversion relationship is as follows:
  • H represents the altitude of the observed surface.
  • the spaceborne remote sensing image expressed by the space rectangular coordinate system (X, Y, Z) is converted into an orthographic projection polar coordinate based on the moon-down point.
  • the ortho-projection polar coordinate system based on the month-down point is defined as follows:
  • Defining the origin O of the spatial coordinate system is the pole of the coordinate system
  • the point o is the intersection of the sensor on the moon and the center of the Earth and the surface of the Earth;
  • the projection surface S is a plane connecting the omission point of the month to the center point of the ground and crossing the origin of the space coordinate system;
  • the direction of the plane S is projected in the direction of the north point of the moon pointing to the north pole point N of the earth.
  • the direction of the polar axis of the coordinate system is 0 degrees;
  • the projection point P' of the point P on the S plane is represented by ⁇ from the length OP' of the pole O. Then, ⁇ is the polar diameter of the point P, and ⁇ is the angle of OP' to OA, and ⁇ is the polar angle of the point P.
  • the cross-platform monthly base-to-earth observation image automatic geometric correction method of the invention utilizes the projection polar coordinate expression based on the moon point to solve the geometric distortion caused by the periodic movement of the moon point, the curvature of the earth and the elevation fluctuation, and retains the moon base pair.
  • the integrity and authenticity of the information from the ground observation image At the same time, the use of on-board observation data solves the problem that the control points are difficult to acquire and distribute unevenly, and the non-manual intervention of the monthly base image automatic geometric correction is realized.
  • FIG. 1 is a flow chart of a method for automatically geometrically correcting a cross-platform moon-based earth observation image of the present invention.
  • FIG. 2 is a flow chart of the step of acquiring the geometric parameters of the moon-based platform.
  • FIG. 3 is a flow chart of the step of expressing the polar coordinates of the on-board remote sensing image based on the point of the moon.
  • Fig. 4 is a schematic diagram showing the projection polar coordinates based on the point of the month.
  • Figure 5 is a flow chart of the month-based platform image simulation step.
  • Figure 6 is a flow chart of the month-based observation and simulation image registration steps.
  • FIG. 1 is a flow chart showing a method for automatically geometrically correcting cross-platform lunar-to-earth observation images of the present invention.
  • the method for automatically geometrically correcting the cross-platform lunar-to-earth observation image of the present invention comprises the step S1 of acquiring the geometric parameters of the moon-based platform, the step S2 of expressing the polar coordinates of the on-board remote sensing image, and the step S3 of the monthly base platform image simulation. And the monthly base observation and analog image registration step S4. The following describes each step in detail.
  • the monthly base-to-ground observation geometric parameters of the observation time are determined by using the sun-moon ground operation relationship, for example, including the month-down point information and the morning faint line information. Specifically, as shown in FIG. 2, the following sub-steps are included:
  • sub-step S11 according to the observation time (T 0 ) and the relationship between the sun and the moon, the information of the month at the observation time, that is, the geographic coordinates (L 0 , B 0 ) of the month is determined.
  • the morning faint line information is determined, and the effective observation range and the day and night range of the moon-based platform at the time are obtained.
  • step S2 of the on-board remote sensing image projection polar coordinate expression the geocoded on-board remote sensing image is expressed as a projection polar coordinate form based on the moon point using the moon-based ground observation geometric parameter obtained in step S1. More specifically, as shown in Figure 3, the following sub-steps are included:
  • sub-step S21 the onboard sensor data of the same or similar type as the moon-based platform sensor is acquired, spliced to form a global geocoded image, and global elevation (DEM) data is acquired.
  • DEM global elevation
  • sub-step S22 according to the effective observation range for the observation time (T 0 ) obtained in step S1, the on-board remote sensing image of the observation area and the DEM information of the corresponding area are obtained, and the geographic information is expressed by the geodetic coordinate system (L, B). , H).
  • sub-step S23 the on-board remote sensing image of the observation area is expressed as a polar coordinate form based on the month-down point.
  • the onboard image expressed by the geodetic coordinate system (L, B, H) in substep S22 is converted into a spatial rectangular coordinate system (X, Y, Z).
  • the conversion relationship between the geodetic coordinate system (L, B, H) and the spatial rectangular coordinate system (X, Y, Z) is as follows:
  • H represents the altitude of the observed surface.
  • the onboard image expressed by the space rectangular coordinate system (X, Y, Z) is converted into an orthographic projection polar coordinate ( ⁇ , ⁇ ) based on the moon's lower point (as shown in the following equation), and the image is saved ( X, Y, Z- ⁇ , ⁇ ) correspondence table.
  • a polar coordinate system is defined, and any point P on the surface of the earth is represented as ( ⁇ , ⁇ ).
  • the polar coordinate system for the moon-based Earth observation remote sensing image is defined as follows:
  • the point o is the intersection of the sensor on the moon and the center of the Earth and the surface of the Earth;
  • the projection surface S is a plane connecting the omission point of the month to the center point of the ground and crossing the origin of the space coordinate system;
  • the direction of the plane S is projected in the direction of the north point of the moon pointing to the north pole point N of the earth.
  • the direction of the polar axis of the coordinate system is 0 degrees;
  • the projection point P of the point P on the S plane is represented by ⁇ from the length OP' of the pole O, then ⁇ is the polar diameter of the point P, and ⁇ is the angle of OP' to OA, and ⁇ is the polar angle of the point P, where 0 ° ⁇ 360°.
  • the moon-based observation of any point on the earth's surface is represented by a spatial Cartesian coordinate system (X, Y, Z), which is expressed in the projected polar coordinate system ( ⁇ , ⁇ ) as follows:
  • (X 0 , Y 0 , Z 0 ) is the known coordinate point of the month
  • (X, Y, Z) is the coordinate value of any point on the ellipsoid
  • (X', Y', Z') is (X) , Y, Z) coordinates on the projection surface S
  • (X' n , Y′ n , Z′ n ) is the coordinate value of the north pole point N on the projection surface S
  • ⁇ is (X, Y, Z) in the projection
  • the polar axis of the surface S polar coordinates, ⁇ is the angle between (X, Y, Z) and (X' n , Y' n , Z' n ) in the S projection plane.
  • the spaceborne remote sensing image expressed by ( ⁇ , ⁇ ) in step S2 is converted into a moon-based platform simulation image by interpolation method.
  • the moon-based platform simulates the image basemap database. Specifically, as shown in FIG. 5, the following sub-steps are included:
  • sub-step S31 the on-board remote sensing image obtained by the ( ⁇ , ⁇ ) obtained in step S2 is interpolated according to the image geometric parameters of the moon-based platform, so that the ⁇ distribution is uniform, and the ⁇ distribution is uniform, and It is consistent with the geometric scale of the observation image of the moon-based platform.
  • the simulated image of the moon-based platform is obtained, and the geometric information is ( ⁇ s , ⁇ s ).
  • sub-step S32 according to the geometric information ( ⁇ s , ⁇ s ) of the simulated image of the moon-based platform, the (X, Y, Z- ⁇ , ⁇ ) correspondence table obtained in step S2 is used to clarify ( ⁇ s , ⁇ s ). Corresponding (X s , Y s , Z s ).
  • sub-step S33 the moon-based platform simulation image and the corresponding ( ⁇ s , ⁇ s -X s , Y s , Z s ) table are stored to form a base-based platform simulation image base map database. Due to the periodicity of the lunar motion, the stored information can be periodically reused.
  • the observation image obtained by the moon-based platform is matched with the simulation image base map corresponding to the observation time, and the geometric correction of the moon-based observation image is completed. Further, as shown in FIG. 6, the following sub-steps are specifically included:
  • sub-step S41 according to the observation time and the monthly period motion law, the corresponding monthly base platform simulation image base map and ( ⁇ s , ⁇ s -X s , Y s are extracted from the monthly base platform simulation image base map database, Z s ) table. If the information is not available in the base map simulation image basemap database, it can be obtained through steps S1, S2, and S3;
  • a registration method suitable for the image type such as a scale-invariant feature conversion method (SIFT)
  • SIFT scale-invariant feature conversion method
  • the cross-platform monthly base-to-earth observation image automatic geometric correction method of the present invention uses the projection polar coordinate expression based on the moon-down point, and introduces the proposed projection polar coordinate expression in the conversion relationship between the moon-based remote sensing image coordinates and the earth coordinate.
  • the introduction of this coordinate has two advantages: on the one hand, the moon-based remote sensing image is expressed by the projected polar coordinates, and its spatial distribution is very close to the remotely sensed image directly obtained by the lunar earth observation, so that the moon-based remote sensing image is registered.
  • the projection polar coordinates the unified calibration model parameters can be established, the registration accuracy and efficiency can be improved, and the influence of the extremely unevenness of the moon-based image control points can be reduced.
  • the expression can effectively reduce the information caused by the moon-based image during coordinate conversion.
  • Loss or information redundancy to achieve information fidelity of the Earth observation hemisphere image, can be used as a standard storage format with geometric information for moon-based remote sensing images.
  • the projected polar coordinates can be conveniently combined with the traditional remote sensing image geographic coordinates to establish a transformation model, and at the same time solve the problem of geometric distortion caused by the movement of the moon, the curvature of the earth and the terrain fluctuation through the transformation model.
  • the geometric positioning accuracy requirements of high-resolution lunar hemisphere images are met.
  • the present invention solves the problem that the control points are difficult to acquire and distribute unevenly by using the onboard observation data, and realizes the automatic geometric correction of the monthly basis image without manual intervention.

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Abstract

通过分析月地关系与月基影像几何畸变的影响因素，着重考虑月下点的位置变化、地球曲率、地形起伏对大尺度半球影像的影响效应，以及地面控制点数量少且分布不均匀问题等，提出面向月基对地观测影像的顾及月下点移动的投影极坐标几何表达方法，并协同多平台对地观测数据，实现月基平台对地观测数据的自动几何精校正。

Description

跨平台月基对地观测影像自动几何校正方法 技术领域
本发明涉及对地观测领域领域，具体涉及一种跨平台月基对地观测影像自动几何校正方法，尤其涉及一种基于月下点投影极坐标表达的跨平台月基对地观测影像自动几何校正方法。
背景技术
为实现星球尺度、长时间连续序列的地球宏观现象的监测，以郭华东院士为首的研究团队提出月基平台对地观测的新思想。月球是地球唯一的自然卫星，在观测地球方面具有整体性和稳定性的特点，为研究地球宏观科学现象提供更为理想的观测平台。然而，月基对地观测在实现瞬时获取半球影像的同时，由于38.4万公里的超远距离、特殊的几何观测条件、月下点移动、星球尺度等因素影响，造成了月基平台获得的对地观测数据的精确几何校正的困难，表现为地球曲率引起的半球尺度影像不同区域的几何形变差异问题，月下点引起的影像中心偏移问题，晨昏线移动引起的观测面积变化问题，以及因大面积海洋、云雾等造成的控制点数量稀少且分布不均匀等问题。
几何校正是将遥感影像坐标与相应地面点坐标建立映射关系，传统的几何校正方法都是适用于局部小区域面积的几何校正，往往忽略地球曲率对几何畸变造成的影响，针对月基对地观测遥感影像的几何校正存在局限，因此针对月基平台的特点，开展适合月基平台对地观测影像的几何校正方法是非常必要且具有重要意义的。
发明内容
本发明公开一种跨平台月基对地观测影像自动几何校正方法，包括以下步骤：月基平台观测几何参数获取步骤，利用日月地运行关系确定观测时刻的月基对地观测几何参数；星载遥感影像投影极坐标表达步骤，利用所述月 基对地观测几何参数，将已经地理编码的星载遥感影像表达为基于月下点的投影极坐标形式；月基平台影像模拟步骤，根据月基平台对地观测影像几何精度要求，通过插值方法将所述极坐标表达的星载遥感影像转换成月基平台模拟影像，形成月基平台模拟影像底图数据库；以及月基观测与模拟影像配准步骤，将所述月基平台获得的观测影像与所述月基平台模拟影像底图数据库中的对应观测时刻的月基平台模拟影像底图进行匹配，完成月基观测影像的几何校正。
本发明的跨平台月基对地观测影像自动几何校正方法中，所述月基对地观测几何参数包括月下点信息和晨昏线信息。
本发明的跨平台月基对地观测影像自动几何校正方法中，所述月基平台观测几何参数获取步骤具体包括以下子步骤：月下点信息获取子步骤，根据观测时间(T 0)和日月地关系，确定观测时刻月下点地理坐标(L 0，B 0)；以及晨昏线信息获取子步骤，根据观测时间和日月地关系，确定观测时刻晨昏线信息，获得该时刻月基平台有效观测范围以及昼夜范围。
本发明的跨平台月基对地观测影像自动几何校正方法中，星载遥感影像投影极坐标表达步骤具体包括以下子步骤：全球高程数据获取子步骤，获取与月基平台传感器类型类似的星载传感器数据，拼接形成全球地理编码影像，获取全球高程数据；观测区域的全球高程数据获取子步骤，根据所述月基平台观测几何参数获取步骤得到的针对观测时刻(T 0)的有效观测范围，获得观测区域的星载遥感影像及相应区域的全球高程数据；基于月下点的极坐标表达子步骤，将所述观测区域的星载遥感影像表达为基于月下点的投影极坐标形式。
本发明的跨平台月基对地观测影像自动几何校正方法中，基于月下点的极坐标表达子步骤包括以下子步骤：将所述星载遥感影像地理信息用大地坐标系表达(L,B,H)；将所述采用大地坐标系(L,B,H)表达的星载遥感影像转换为空间直角坐标系(X,Y,Z)；以及将所述用空间直角坐标系(X,Y,Z)表达的星载遥感影 像转换为基于月下点的正射投影极坐标(ρ,θ)，并保存该影像的(X,Y,Z-ρ,θ)对应表；
Figure PCTCN2018088154-appb-000001
S:X·X 0+Y·Y 0+Z·Z 0＝0    (5)
Figure PCTCN2018088154-appb-000002
其中，(X 0,Y 0,Z 0)为已知的月下点坐标值，(X,Y,Z)为椭球面上任一点坐标值，(X′,Y′,Z′)为(X,Y,Z)在投影面S上的坐标，(X′ n, ′Y′ n,Z′ n)为北极点N在投影面S上的坐标值，ρ是(X,Y,Z)在投影面S极坐标下的极轴，θ是(X,Y,Z)和(X′ n,Y′ n,Z′ n)在S投影面中的夹角。
本发明的跨平台月基对地观测影像自动几何校正方法中，所述月基平台影像模拟步骤具体包括以下子步骤：根据月基平台观测影像几何参数，对所述用极坐标(ρ,θ)表达的星载遥感影像进行插值，使其满足ρ分布均匀，ρ·Δθ分布均匀，且与月基平台观测影像几何尺度一致，插值后得到月基平台模拟影像，其几何信息为(ρ s,θ s)；根据所述月基平台模拟影像的几何信息(ρ s,θ s)，利用所述(X,Y,Z-ρ,θ)对应表，明确所述月基平台模拟影像的几何信息(ρ s,θ s)对应的(X s,Y s,Z s)；以及将所述月基平台模拟影像及对应的(ρ s,θ s-X s,Y s,Z s)表存入月基平台模拟影像底图数据库。
本发明的跨平台月基对地观测影像自动几何校正方法中，所述月基平台观测与模拟影像配准步骤具体包括以下子步骤：根据观测时间及月地周期运动规律，从所述月基平台模拟影像底图数据库中提取对应的月基平台模拟影像底图及(ρ s,θ s-X s,Y s,Z s)表；选择适用于所述月基平台观测影像类型的配准方法，将所述月基平台观测影像配准到所述月基平台模拟影像底图，完成所述月基平台观测影像的几何校正。
本发明的跨平台月基对地观测影像自动几何校正方法中，所述配准方法 为尺度不变特征转换方法。
本发明的跨平台月基对地观测影像自动几何校正方法中，采用顾及地表高度的参考椭球体为地球参考模型时，大地坐标系(L,B,H)与空间直角坐标系(X,Y,Z)的转换关系如下：
X＝(N+H)·cos B·cos L  （1)
Y＝(N+H)·cos B·sin L  (2)
Z＝[H·(1-e 2)+H]·sin B  (3)
其中，H代表观测地表的海拔高度。
本发明的跨平台月基对地观测影像自动几何校正方法中，将所述用空间直角坐标系(X,Y,Z)表达的星载遥感影像转换为基于月下点的正射投影极坐标(ρ,θ)步骤中，所述的基于月下点的正射投影极坐标系定义如下：
定义空间坐标系的原点O为坐标系的极点；
月下点o是月球上的布设的传感器与地球中心连线与地球表面的交点；
投影面S为月下点与地中心点连线oO且过空间坐标系原点的平面；
以月下点o指向地球北极点N的方向ON在平面S的投影方向
Figure PCTCN2018088154-appb-000003
为坐标系极轴0度方向；
对椭球面一点P，其弧长
Figure PCTCN2018088154-appb-000004
长度用l表示；
P点在S平面的投影点P′距极点O的长度OP′用ρ表示，则ρ为P点的极径，θ表示OP′到OA的角度，则θ为点P的极角。
本发明的跨平台月基对地观测影像自动几何校正方法利用基于月下点的投影极坐标表达，解决了月下点周期移动、地球曲率和高程起伏引起的几何畸变问题，保留了月基对地观测影像的信息的完整性和真实性。同时，利用星载观测数据，解决了控制点难以获取和分布不均匀问题，实现非人工干预月基影像自动几何校正。
附图说明
图1是本发明的跨平台月基对地观测影像自动几何校正方法的流程图。
图2是月基平台观测几何参数获取步骤的流程图。
图3是星载遥感影像基于月下点的投影极坐标表达步骤的流程图。
图4是基于月下点的投影极坐标表达示意图。
图5是月基平台影像模拟步骤的流程图。
图6是月基观测与模拟影像配准步骤的流程图。
具体实施方式
为了使本发明的目的、技术方案及优点更加清楚明白，下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，应当理解，此处所描述的具体实施例仅用以解释本发明，并不用于限定本发明。所描述的实施例仅仅是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其它实施例，都属于本发明保护的范围。
图1中示出了本发明的跨平台月基对地观测影像自动几何校正方法的流程图。如图1所示，本发明的跨平台月基对地观测影像自动几何校正方法包括月基平台观测几何参数获取步骤S1，星载遥感影像投影极坐标表达步骤S2，月基平台影像模拟步骤S3以及月基观测与模拟影像配准步骤S4。以下针对各步骤进行具体说明。
在月基平台观测几何参数获取步骤S1中，利用日月地运行关系确定观测时刻的月基对地观测几何参数，例如包括月下点信息和晨昏线信息。具体而言，如图2所示，包括以下子步骤：
在子步骤S11中，根据观测时间(T 0)和日月地关系，确定观测时刻月下点信息，即月下点地理坐标(L 0，B 0)。
在子步骤S12中，根据观测时间和日月地关系，确定该时刻晨昏线信息，获得该时刻月基平台有效观测范围以及昼夜范围。
在星载遥感影像投影极坐标表达步骤S2中，利用步骤S1中得到的月基 对地观测几何参数，将已经地理编码的星载遥感影像表达为基于月下点的投影极坐标形式。更具体地来说，如图3所示，包括以下子步骤：
在子步骤S21中，获取与月基平台传感器类型相同或类似的星载传感器数据，拼接形成全球地理编码影像，获取全球高程(DEM)数据。
在子步骤S22中，根据步骤S1中得到的针对观测时间(T 0)的有效观测范围，获得观测区域的星载遥感影像及相应区域的DEM信息，地理信息用大地坐标系表达(L,B,H)。
在子步骤S23中，将观测区域的星载遥感影像表达为基于月下点的极坐标形式。具体而言，将子步骤S22中用大地坐标系(L,B,H)表达的星载影像转换为空间直角坐标系(X,Y,Z)。采用顾及地表高度的参考椭球体为地球参考模型时，大地坐标系(L,B,H)与空间直角坐标系(X,Y,Z)的转换关系如下：
X＝(N+H)·cos B·cos L  (1)
Y＝(N+H)·cos B·sin L  (2)
Z＝[N·(1-e 2)+H]·sin B  (3)
其中，H代表观测地表的海拔高度。
然后，将用空间直角坐标系(X,Y,Z)表达的星载影像转换为基于月下点的正射投影极坐标(ρ,θ)(如下式所示)，并保存该影像的(X,Y,Z-ρ,θ)对应表。
具体而言，首先，定义极坐标系，将地球表面的任意一点P表示为(ρ，θ)。如图4所示，面向月基对地观测遥感影像的极坐标系具体定义如下：
定义空间坐标系的原点O为极点；
月下点o是月球上的布设的传感器与地球中心连线与地球表面的交点；
投影面S为月下点与地中心点连线oO且过空间坐标系原点的平面；
以月下点o指向地球北极点N的方向ON在平面S的投影方向
Figure PCTCN2018088154-appb-000005
为坐标系极轴0度方向；
对椭球面一点P，其弧长
Figure PCTCN2018088154-appb-000006
长度用l表示；
P点在S平面的投影点P′距极点O的长度OP′用ρ表示，则ρ为P点的极径，θ表示OP′到OA的角度，则θ为点P的极角，其中0°≤θ<360°。
接下来，建立月基对地观测影像投影极坐标和空间直角坐标系之间的转换关系。月基观测地球表面上的任一点用空间直角坐标系(X,Y,Z)表示，则该点用投影极坐标系(ρ，θ)表达如下：
Figure PCTCN2018088154-appb-000007
S:X·X 0+Y·Y 0+Z·Z 0＝0  (5)
Figure PCTCN2018088154-appb-000008
其中，(X 0,Y 0,Z 0)为已知的月下点坐标值，(X,Y,Z)为椭球面上任一点坐标值，(X′,Y′,Z′)为(X,Y,Z)在投影面S上的坐标，(X′ n,Y′ n,Z′ n)为北极点N在投影面S上的坐标值，ρ是(X,Y,Z)在投影面S极坐标下的极轴，θ是(X,Y,Z)和(X′ n,Y′ n,Z′ n)在S投影面中的夹角。在图4中示出了基于月下点的投影极坐标表达示意图。
在月基平台影像模拟步骤S3中，根据月基平台对地观测影像几何精度要求，通过插值方法将步骤S2中用(ρ,θ)表达的星载遥感影像转换为月基平台模拟影像，形成月基平台模拟影像底图数据库。具体而言，如图5所示，包括以下子步骤：
在子步骤S31中，根据月基平台观测影像几何参数，对步骤S2中获得的用(ρ,θ)表达的星载遥感影像进行插值，使其满足ρ分布均匀，ρ·Δθ分布均匀，且与月基平台观测影像几何尺度一致，插值后得到月基平台模拟影像，其几何信息为(ρ s,θ s)。
在子步骤S32中，根据月基平台模拟影像的几何信息(ρ s,θ s)，利用步骤S2得到的(X,Y,Z-ρ,θ)对应表，明确(ρ s,θ s)对应的(X s,Y s,Z s)。
在子步骤S33中，将月基平台模拟影像及对应的(ρ s,θ s-X s,Y s,Z s)表存储形成月基平台模拟影像底图数据库。由于月地运动存在周期性，该存储信息可以周期重复利用。
在月基观测与模拟影像配准步骤S4中，将该月基平台获得的观测影像与观测时刻对应的模拟影像底图进行匹配，完成月基观测影像的几何校正。进一步来说，如图6所示，具体包括以下子步骤：
在子步骤S41中，根据观测时间及月地周期运动规律，从月基平台模拟影像底图数据库中提取对应的月基平台模拟影像底图及(ρ s,θ s-X s,Y s,Z s)表。若月基平台模拟影像底图数据库中没有该信息，可通过步骤S1、S2、S3获得；
在子步骤S42中，选择适用于该影像类型的配准方法，例如尺度不变特征转换方法(SIFT)，将月基平台观测影像配准到月基平台模拟影像底图，完成月基平台观测影像的几何校正。
本发明的跨平台月基对地观测影像自动几何校正方法利用基于月下点的投影极坐标表达，在月基遥感影像坐标与大地坐标的转换关系中，引入所提出的投影极坐标表达，作为二者之间的中间坐标。该坐标的引入有两方面的优势：一方面月基遥感影像用所发明的投影极坐标表达，其空间分布特征十分接近月球对地观测直接获得的遥感影像，从而在将月基遥感图像配准到该投影极坐标时，能够建立统一校正模型参数，提高配准精度和效率，减少月基影像控制点极不均匀的影响；同时该表达方式能够有效减少月基影像在坐标转换时造成的信息丢失或者信息冗余，实现对地观测半球影像的信息保真，可以作为月基遥感影像的一种带几何信息的标准存储格式。另一方面所发明的投影极坐标能够方便的与传统遥感影像地理坐标之间的建立对应转换模型，同时通过转换模型解决月下点移动、地球曲率、地形起伏带来的几何畸变等问题。最终满足高分辨率月基半球影像的几何定位精度要求。
此外，本发明利用星载观测数据，解决了控制点难以获取和分布不均匀问题，实现非人工干预月基影像自动几何校正。
以上所述，仅为本发明的具体实施方式，但本发明的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本发明揭露的技术范围内，可轻易想到的变化或替换，都应涵盖在本发明的保护范围之内。

Claims (10)

  1. 一种跨平台月基对地观测影像自动几何校正方法，其特征在于，
    包括以下步骤：
    月基平台观测几何参数获取步骤，利用日月地运行关系确定观测时刻的月基对地观测几何参数；
    星载遥感影像投影极坐标表达步骤，利用所述月基对地观测几何参数，将已经地理编码的星载遥感影像表达为基于月下点的投影极坐标形式；
    月基平台影像模拟步骤，根据月基平台对地观测影像几何精度要求，通过插值方法将所述极坐标表达的星载遥感影像转换成月基平台模拟影像，形成月基平台模拟影像底图数据库；以及
    月基观测与模拟影像配准步骤，将所述月基平台获得的观测影像与所述月基平台模拟影像底图数据库中的对应观测时刻的月基平台模拟影像底图进行匹配，完成月基观测影像的几何校正。
  2. 根据权利要求1所述的跨平台月基对地观测影像自动几何校正方法，其特征在于，
    所述月基对地观测几何参数包括月下点信息和晨昏线信息。
  3. 根据权利要求2所述的跨平台月基对地观测影像自动几何校正方法，其特征在于，
    所述月基平台观测几何参数获取步骤具体包括以下子步骤：
    月下点信息获取子步骤，根据观测时间(T 0)和日月地关系，确定观测时刻月下点地理坐标(L 0，B 0)；以及
    晨昏线信息获取子步骤，根据观测时间和日月地关系，确定观测时刻晨昏线信息，获得该时刻月基平台有效观测范围以及昼夜范围。
  4. 根据权利要求3所述的跨平台月基对地观测影像自动几何校正方法，其特征在于，
    星载遥感影像投影极坐标表达步骤具体包括以下子步骤：
    全球高程数据获取子步骤，获取与月基平台传感器类型类似的星载传感器数据，拼接形成全球地理编码影像，获取全球高程数据；
    观测区域的全球高程数据获取子步骤，根据所述月基平台观测几何参数获取步骤得到的针对观测时刻的有效观测范围，获得观测区域的星载遥感影像及相应区域的全球高程数据；
    基于月下点的投影极坐标表达子步骤，将所述观测区域的星载遥感影像表达为基于月下点的投影极坐标形式。
  5. 根据权利要求4所述的跨平台月基对地观测影像自动几何校正方法，其特征在于，
    基于月下点的极坐标表达子步骤包括以下子步骤：
    将所述星载遥感影像地理信息用大地坐标系表达(L,B,H)；
    将所述采用大地坐标系(L,B,H)表达的星载遥感影像转换为空间直角坐标系(X,Y,Z)；以及
    将所述用空间直角坐标系(X,Y,Z)表达的星载遥感影像转换为基于月下点的正射投影极坐标(ρ,θ)，并保存该影像的(X,Y,Z-ρ,θ)对应表，
    Figure PCTCN2018088154-appb-100001
    S：X·X 0+Y·Y 0+Z·Z 0＝0………    (5)
    Figure PCTCN2018088154-appb-100002
    其中，(X 0,Y 0,Z 0)为已知的月下点坐标值，(X,Y,Z)为椭球面上任一点坐标值，(X′,Y′,Z′)为(X,Y,Z)在投影面S上的坐标，(X′ n,Y′ n,Z′ n)为北极点N在投影面S上的坐标值，ρ是(X,Y,Z)在投影面S极坐标下的极轴，θ是(X,Y,Z)和(X′ n,Y′ n,Z′ n)在S投影面中的夹角。
  6. 根据权利要求4所述的跨平台月基对地观测影像自动几何校正方法，其特征在于，
    所述月基平台影像模拟步骤具体包括以下子步骤：
    根据月基平台观测影像几何参数，对所述用极坐标(ρ,θ)表达的星载遥感影像进行插值，使其满足ρ分布均匀，ρ·Δθ分布均匀，且与月基平台观测影像几何尺度一致，插值后，得到月基平台模拟影像，其几何信息为(ρ S,θ S)；
    根据所述月基平台模拟影像的几何信息(ρ S,θ S)，利用所述(X,Y,Z-ρ,θ)对应表，明确所述月基平台模拟影像的几何信息(ρ S,θ S)对应的(X s,Y s,Z s)；以及
    将所述月基平台模拟影像及对应的(ρ S,θ S-X s,Y s,Z s)表存入月基平台模拟影像底图数据库。
  7. 根据权利要求6所述的跨平台月基对地观测影像自动几何校正方法，其特征在于，
    所述月基平台观测与模拟影像配准步骤具体包括以下子步骤：
    根据观测时间及月地周期运动规律，从所述月基平台模拟影像底图数据库中提取对应的月基平台模拟影像底图及(ρ S,θ S-X s,Y s,Z s)表；
    选择适用于所述月基平台观测影像类型的配准方法，将所述月基平台观测影像配准到所述月基平台模拟影像底图，完成所述月基平台观测影像的几何校正。
  8. 根据权利要求7所述的跨平台月基对地观测影像自动几何校正方法，其特征在于，
    所述配准方法为尺度不变特征转换方法。
  9. 根据权利要求5所述的跨平台月基对地观测影像自动几何校正方法，其特征在于，
    采用顾及地表高度的参考椭球体为地球参考模型时，大地坐标系(L,B,H)与空间直角坐标系(X,Y,Z)的转换关系如下：
    X＝(N+H)·cos B·cos L    (1)
    Y＝(N+H)·cos B·sin L    (2)
    Z＝[N·(1-e 2)+H]·sin B    (3)
    其中，H代表观测地表的海拔高度。
  10. 根据权利要求5所述的跨平台月基对地观测影像自动几何校正方法，其特征在于，
    将所述用空间直角坐标系(X,Y,Z)表达的星载遥感影像转换为基于月下点的正射投影极坐标(ρ,θ)步骤中，所述的基于月下点的正射投影极坐标系定义如下：
    定义空间坐标系的原点O为坐标系的极点；
    月下点o是月球上的布设的传感器与地球中心连线与地球表面的交点；
    投影面S为月下点与地中心点连线oO且过空间坐标系原点的平面；
    以月下点o指向地球北极点N的方向ON在平面S的投影方向
    Figure PCTCN2018088154-appb-100003
    为坐标系极轴0度方向；
    对椭球面一点P，其弧长
    Figure PCTCN2018088154-appb-100004
    长度用l表示；
    P点在S平面的投影点P′距极点O的长度OP′用ρ表示，则ρ为P点的极径，θ表示OP′到OA的角度，则θ为点P的极角。
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