WO2019205751A1 - Image enhancement method - Google Patents

Abstract

An image enhancement method, the method comprising: performing defogging on a first image to obtain a target image (101); based on a pre-set strategy, determining, from multiple pre-set image enhancement algorithms, a target image enhancement algorithm adaptable for a brightness feature of the target image (102); and performing image enhancement on the target image based on the target image enhancement algorithm (103).

Description

Image enhancement method

Cross-reference to related applications

The present application claims priority to Chinese Patent Application No. 20,181, 038, 752, filed on Apr. 26, 20, the entire disclosure of which is incorporated herein by reference. Incorporated herein.

Technical field

Embodiments of the present disclosure relate to the field of image processing technologies, and more particularly to image enhancement processing of a defogged image.

Background technique

Generally, after defogging a fogged image, the overall brightness of the image is low, and image enhancement processing is required. At present, methods of image enhancement processing mainly include, for example, an automatic gradation method, an automatic contrast method, and the like. The automatic gradation method first determines the upper/lower limit ratio of the image color, calculates a histogram of the image; then sets the pixel value of the pixel whose pixel value is lower than the lower limit ratio in the image to 0, and the pixel whose pixel value is higher than the upper limit ratio The value is set to 255 and the pixel values of the pixels whose pixel values are between the lower scale ratio and the upper scale ratio are linearly transformed. However, due to the different image pixel value distribution intervals of different images, the fixed color threshold cannot automatically adapt to the image. In addition, calculating the histogram takes a long time.

Summary of the invention

Embodiments of the present disclosure provide an image enhancement method, apparatus, device, and storage medium for improving image enhancement effects on a defogged image and reducing complexity of image enhancement processing.

A first aspect of the embodiments of the present disclosure provides an image enhancement method, including:

Defogging the first image to obtain a target image;

Determining, from a plurality of preset image enhancement algorithms, a target image enhancement algorithm that is adapted to the brightness characteristics of the target image based on a preset strategy;

Image enhancement processing is performed on the target image based on the target image enhancement algorithm.

Optionally, the multiple preset image enhancement algorithms include: a linear transformation algorithm, an automatic transformation algorithm, a logarithmic transformation algorithm, and a gamma transformation algorithm.

Optionally, the brightness characteristic of the target image includes an average brightness of the target image as a whole;

Determining, according to a preset strategy, a target image enhancement algorithm that is adapted to the brightness feature of the target image from a plurality of preset image enhancement algorithms, including:

If the average brightness of the target image as a whole is less than a first preset threshold, determining that the automatic transform algorithm is a target image enhancement algorithm;

And if the average brightness of the target image as a whole is greater than the first preset threshold and less than the second preset threshold, determining that the logarithmic transformation algorithm or the gamma transformation algorithm is the target image enhancement algorithm.

Optionally, the brightness characteristic of the target image includes respective average brightness of different regions on the target image.

And performing image enhancement processing on the target image based on the target image enhancement algorithm, including:

And performing image enhancement processing on the region based on a target image enhancement algorithm adapted to an average brightness of the region for different regions on the target image;

or

The image enhancement processing is repeatedly performed on the target image as a whole based on a plurality of target image enhancement algorithms respectively corresponding to different regions on the target image.

A second aspect of the embodiments of the present disclosure provides an image enhancement apparatus, including:

a defogging module, configured to perform a defogging process on the first image to obtain a target image;

a determining module, configured to determine, according to a preset policy, a target image enhancement algorithm that is adapted to a brightness feature of the target image from among a plurality of preset image enhancement algorithms;

And a processing module, configured to perform image enhancement processing on the target image based on the target image enhancement algorithm.

Optionally, the multiple preset image enhancement algorithms include: a linear transformation algorithm, an automatic transformation algorithm, a logarithmic transformation algorithm, and a gamma transformation algorithm.

Optionally, the brightness characteristic of the target image includes an average brightness of the target image as a whole;

The determining module includes:

a first determining submodule, configured to determine that the automatic transform algorithm is a target image enhancement algorithm when an average brightness of the target image as a whole is less than a first preset threshold;

The second determining submodule is configured to determine that the logarithmic transform algorithm or the gamma transform algorithm is the target image enhancement algorithm when the average brightness of the target image as a whole is greater than the first preset threshold and less than the second preset threshold.

Optionally, the brightness characteristic of the target image includes an average brightness of different regions on the target image;

The processing module includes:

a first processing submodule, configured to perform image enhancement processing on the region based on a target image enhancement algorithm that is adapted to an average brightness of the region for different regions on the target image;

or

The second processing submodule is configured to repeatedly perform image enhancement processing on the target image as a whole based on a plurality of target image enhancement algorithms respectively corresponding to different regions on the target image.

A third aspect of the embodiments of the present disclosure provides a mobile terminal, including:

processor;

a memory for storing machine executable instructions and image data;

The method of the first aspect described above is implemented when the processor executes the machine executable instructions.

A fourth aspect of embodiments of the present disclosure provides a computer readable non-volatile storage medium comprising instructions that, when executed on a processor, implement the method of the first aspect described above.

DRAWINGS

In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the drawings used in the description of the embodiments will be briefly described below. It is obvious that the drawings in the following description are only some embodiments of the present disclosure. Other drawings may also be obtained from those of ordinary skill in the art in light of the inventive work.

FIG. 1 is a flowchart of an image enhancement method according to an embodiment of the present disclosure.

FIG. 2 is a flowchart of an image enhancement method according to an embodiment of the present disclosure.

FIG. 3 is a flowchart of an image enhancement method according to an embodiment of the present disclosure.

FIG. 4 is a schematic structural diagram of an image enhancement apparatus according to an embodiment of the present disclosure.

FIG. 5 is a schematic structural diagram of an image enhancement apparatus according to an embodiment of the present disclosure.

FIG. 6 is a schematic structural diagram of an image enhancement apparatus according to an embodiment of the present disclosure.

FIG. 7 is a schematic structural diagram of a terminal device according to an embodiment of the present disclosure.

detailed description

Images collected in bad weather such as fog and fog are severely degraded due to the effects of atmospheric scattering. Object features are difficult to recognize and visual effects are degraded, which may affect the processing of images later. Therefore, image defogging technology is needed to enhance or repair to improve the visual effect of the image and facilitate post processing. In general, image defogging methods may have image enhancement based methods and physical model based methods. There are various methods of image de-fogging based on image enhancement, such as image defogging algorithms with dark channel priors. According to the conventional image enhancement-based image dehazing algorithm, the image obtained by demisting the image has a low overall brightness and a poor visual effect.

Embodiments of the present disclosure provide an image enhancement method. The method can be performed by an image enhancement device that is mounted on a terminal having image processing functions, such as a cell phone, a traffic camera, and the like. Referring to FIG. 1 , FIG. 1 is a flowchart of an image enhancement method according to an embodiment of the present disclosure. As shown in FIG. 1 , the method includes the following steps.

Step 101: Perform a defogging process on the first image to obtain a target image.

The name of the “first image” in this embodiment is only used to distinguish the image to be defogged from other images, and does not have other meanings. The target image refers to an image obtained after the first image has undergone dehazing.

Here, the preliminary image defogging process may be performed on the first image according to a preset image defogging algorithm to obtain a target image after the defogging process. In a subsequent step, the target image is subjected to image enhancement processing using an image enhancement method according to an embodiment of the present disclosure to obtain a desired image. In the embodiment of the present disclosure, the image dehazing algorithm employed is not limited. In fact, the image enhancement method of the present disclosure can be applied to almost all images obtained after dehazing.

Step 102: Determine, according to a preset policy, a target image enhancement algorithm that is adapted to the brightness feature of the target image from the plurality of preset image enhancement algorithms.

The luminance characteristics of the target image involved in the embodiment include average luminance information of the entire target image, or average luminance information of different regions on the target image. The image enhancement algorithms involved in this embodiment include, but are not limited to, a linear transformation algorithm, an automatic transformation algorithm, a logarithmic transformation algorithm, and a gamma transformation algorithm.

The image enhancement algorithm according to this embodiment can be understood as a grayscale transformation algorithm. The gradation transformation algorithm refers to a method of changing the gradation value of each pixel in the source image pixel by pixel according to a certain transformation condition according to a certain transformation relationship. The gradation transformation algorithm can be divided into a linear transformation algorithm and a nonlinear transformation algorithm.

Among them, the linear transformation algorithm can be expressed by the following expression (1):

表示经线性变换后的该像素点x的灰度值，a表示如上式(1)的线性变换函数的斜率，b表示纵截距，a,b均为常数。当a＝1且b≠0时，经过该线性变换，目标图像整体的灰度值发生了偏移，也就是目标图像整体的亮度变亮或变暗，不会改变目标图像的对比度；当a>1时，可以增加图像的对比度。 Where x represents any pixel in the target image, and I(x) represents the gray value of the pixel x.

The gradation value of the linearly transformed pixel x is represented, a represents the slope of the linear transformation function of the above formula (1), b represents the vertical intercept, and a and b are constants. When a=1 and b≠0, the linear value of the target image is shifted by the linear transformation, that is, the brightness of the entire target image is brightened or darkened, and the contrast of the target image is not changed; >1, you can increase the contrast of the image.

The nonlinear transform algorithm includes, for example, an automatic transform algorithm, a logarithmic transform algorithm, a gamma transform algorithm, and the like.

Optionally, the gamma transform algorithm may be represented by the following expression (2):

表示经伽马变换后的该像素点的灰度值，c、r为正常数。其中，当r<1时，r值越小，对目标图像中低灰度值的像素点的灰度范围扩展越明显，使得像素的动态范围增加，显示的图像更加清晰。 Where I(x) represents the gray value of the pixel point x in the target image,

Indicates the gradation value of the pixel after gamma conversion, and c and r are normal numbers. Wherein, when r<1, the smaller the r value is, the more obvious the gray range expansion of the pixel points of the low gray value in the target image is, so that the dynamic range of the pixel is increased, and the displayed image is more clear.

Optionally, the logarithmic transformation algorithm may be represented by the following expression (3):

Where d is a constant, and the logarithmic transformation algorithm can map a narrow gray value in the target image to a wide gray range, and map a wide grayscale interval to a narrower range. The grayscale interval, which extends the value of the dark pixel, compresses the value of the high grayscale, and enhances the low grayscale detail in the image.

Optionally, the automatic transformation algorithm may be represented by the following expression (4):

When performing the automatic transform algorithm, it is necessary to normalize the gray value of the pixel in the target image to [0, 1]. In the automatic transformation algorithm, the amount of gray value increase of the pixel in the target image is symmetric with respect to 0.5, and the growth amount gradually increases in the interval of [0, 0.5], and the growth amount becomes smaller in the interval of [0.5, 1], thereby realizing The image as a whole becomes brighter.

The preset policy referred to in this embodiment refers to a correspondence between a preset image enhancement algorithm and a target image brightness feature. For example, when the average brightness of the target image is less than the first preset threshold, the image enhancement process may be performed on the target image by using an automatic transformation algorithm. When the average brightness of the target image is greater than the first preset threshold and less than the second preset threshold, the image enhancement processing may be performed on the target image by using a logarithmic transformation algorithm or a gamma transformation algorithm. When the average brightness of a certain area on the target image is less than the fourth threshold, and the average brightness of the other area is greater than the fifth threshold, wherein the fifth threshold is greater than the fourth threshold, the image of the target image may be performed by using a linear transformation algorithm. Enhanced processing. Of course, the above is merely illustrative and not limiting. In fact, the correspondence between the image brightness feature and the image enhancement algorithm can be set as needed. For example, in one design, an image brightness feature can also correspond to multiple image enhancement algorithms, thereby using multiple image enhancements. The algorithm implements image enhancement processing on the target image.

Step 103: Perform image enhancement processing on the target image based on the target image enhancement algorithm.

In this embodiment, the target image is obtained by performing a defogging process on the first image, and the target image enhancement algorithm that is adapted to the brightness feature of the target image is determined from the plurality of preset image enhancement algorithms based on the preset strategy, thereby The target image enhancement algorithm performs image enhancement processing on the target image. In this embodiment, a plurality of image enhancement algorithms are preset for different image brightness features. When the target image obtained after the defogging process is subjected to image enhancement processing, it may be targeted from a plurality of presets according to a preset strategy. An image enhancement algorithm adapted to the brightness characteristics of the target image is selected in the image enhancement algorithm to process the target image. Therefore, it is possible to achieve a better image enhancement effect without setting the upper/lower limit ratio of the image color, and it is not necessary to perform histogram calculation, which reduces the complexity of the image enhancement processing.

FIG. 2 is a flowchart of an image enhancement method according to an embodiment of the present disclosure. As shown in FIG. 2, on the basis of the embodiment of FIG. 1, the method includes the following steps.

Step 201: Acquire an average brightness of the entire target image.

Step 202a: If the average brightness of the target image as a whole is less than a first preset threshold, determine that the automatic transform algorithm is a target image enhancement algorithm.

In this embodiment, when the average brightness of the target image is less than the first preset threshold, the overall brightness of the target image is considered to be dark. At this time, the image is enhanced by using an automatic transform algorithm, which can greatly improve the brightness of the target image. And it can be seen from the above embodiment that the automatic transformation algorithm can be expressed by the following expression:

Therefore, when the image enhancement processing is performed on the target image by using the automatic transformation algorithm, it is not necessary to separately set parameters, and the operation is convenient, and the efficiency of the image enhancement processing can be improved.

Step 202b: If the average brightness of the target image as a whole is greater than the first preset threshold and less than the second preset threshold, determine that the logarithmic transformation algorithm or the gamma transformation algorithm is the target image enhancement algorithm.

The second preset threshold is greater than the first preset threshold, and the values of the first preset threshold and the second preset threshold may be set as needed.

In this embodiment, when the average brightness of the target image is greater than the first preset threshold, the overall brightness of the target image is not particularly dark, and the brightness of the target image may be increased as appropriate. Good performance. And since both the gamma transform algorithm and the logarithmic transform algorithm can significantly expand the low gray value in the image and display more low gray value details, the gamma transform algorithm or the logarithmic transform algorithm can be used in this embodiment. The image enhancement processing is performed on the target image whose average brightness is greater than the first preset threshold and less than the second preset threshold, thereby obtaining a better image enhancement effect. Among them, compared with the gamma conversion algorithm, the logarithmic transformation algorithm can achieve better results.

Step 203: Perform image enhancement processing on the target image based on the target image enhancement algorithm.

In this embodiment, by performing image enhancement processing on the target image by using a gamma conversion algorithm or a logarithmic transformation algorithm when the average luminance value of the entire target image is greater than the first threshold is less than the second threshold, the low gray value in the target image can be made. The portion is significantly enhanced to achieve better image enhancement.

FIG. 3 is a flowchart of an image enhancement method according to an embodiment of the present disclosure. As shown in FIG. 3, on the basis of the embodiment of FIG. 1, the method includes the following steps.

Step 301: Acquire an average brightness of different regions on the target image.

Step 302: Determine, for each region on the target image, an image enhancement algorithm that is adapted to the average brightness of the region from the plurality of preset image enhancement algorithms based on the preset policy. Target image enhancement algorithm.

Step 303: Perform image enhancement processing on the target image based on a target image enhancement algorithm respectively determined for each region.

Since the average brightness of different regions may be different, the target image enhancement algorithm determined in this embodiment may be multiple. When image enhancement processing is performed on a target image based on a plurality of target image enhancement algorithms, the implementation includes the following.

In a first implementation, an image enhancement process may be performed on the region based on a target image enhancement algorithm that is commensurate with the average brightness of the region for each region on the target image until all regions are processed and stopped.

In another implementation, the target image may be subjected to multiple image enhancement processes based on the determined plurality of target image enhancement algorithms. For example, it is assumed that the target image includes a first area and a second area, wherein the average brightness of the first area is less than a third preset threshold, and the average brightness of the second area is greater than a fourth preset threshold, wherein the fourth preset threshold Greater than the third preset threshold. At this time, it is determined that the linear transformation algorithm and the logarithmic transformation algorithm are target image enhancement algorithms. Further, the first image enhancement processing may be performed on the target image based on one of the linear transformation algorithm and the logarithmic transformation algorithm, and then the second image enhancement processing is performed on the target image based on the other of the two. , get the final image.

Specifically, the third preset threshold is used to determine whether the image is too dark, and the fourth preset threshold is used to determine that the image is too bright. When the average brightness of an area on the image is less than the third preset threshold, it indicates that the brightness of the area is too dark; when the average brightness of another area on the image is greater than the fourth preset threshold, it indicates that the brightness of the area is too bright. Based on this, when the first image and the second region involved above are included on the target image, it is explained that the target image includes an area that is too dark (ie, a first area) and an area that is too bright (ie, a second area). At this time, if the automatic transform algorithm, the gamma transform algorithm or the logarithmic transform algorithm is used, the brightness improvement effect on the first region and the second region is small, and the linear transform algorithm can significantly enhance the brightness in the image which is too dark or too strong. The display effect and the display effect of other areas in the image can be appropriately improved. Therefore, the present embodiment can perform image enhancement processing on the target image by using a linear transformation algorithm. Specifically, the parameter b in the linear transformation algorithm (1) described above may be set to a different value for the first region and the second region, respectively, and then the first region and the second region are respectively subjected to gradation transformation processing.

However, if only the image transformation processing is performed on the target image by using a linear transformation algorithm, although the region where the luminance is between the first region and the second region can be enhanced, the enhancement effect is limited, considering the logarithm. The transform can perform the enhancement processing on the region. Therefore, in this embodiment, after the image enhancement processing is performed on the target image by using the linear transform algorithm, the logarithmic transformation algorithm is used to compare the brightness between the first region and the second region. The area between the areas is further enhanced in brightness to achieve an overall improvement in image brightness.

The above examples are of course only illustrative and not limiting of the disclosure.

In this embodiment, by determining a plurality of target image enhancement algorithms based on average brightness of different regions on the target image, and performing image enhancement processing on the target image based on the plurality of target image enhancement algorithms, the defects of the single image enhancement algorithm can be avoided. The brightness effect of the target image as a whole is enhanced.

FIG. 4 is a schematic structural diagram of an image enhancement apparatus according to an embodiment of the present disclosure. As shown in FIG. 4, the apparatus includes the following modules.

The defogging module 41 is configured to perform a defogging process on the first image to obtain a target image.

The determining module 42 is configured to determine, from the plurality of preset image enhancement algorithms, a target image enhancement algorithm that is adapted to the brightness feature of the target image based on the preset policy.

The processing module 43 is configured to perform image enhancement processing on the target image based on the target image enhancement algorithm.

Optionally, the multiple preset image enhancement algorithms include: a linear transformation algorithm, an automatic transformation algorithm, a logarithmic transformation algorithm, and a gamma transformation algorithm.

The image enhancement apparatus provided in this embodiment can perform the method of the embodiment of FIG. 1. Other implementation modes and beneficial effects are similar, and details are not described herein again.

FIG. 5 is a schematic structural diagram of an image enhancement apparatus according to an embodiment of the present disclosure. As shown in FIG. 5, on the basis of the embodiment of FIG. 4, the brightness characteristic of the target image includes an average brightness of the target image as a whole; The determining module 42 includes:

The first determining sub-module 421 is configured to determine, when the average brightness of the target image as a whole is less than a first preset threshold, that the automatic transform algorithm is a target image enhancement algorithm;

The second determining sub-module 422 is configured to determine that the logarithmic transform algorithm or the gamma transform algorithm is the target image enhancement algorithm when the average brightness of the target image is greater than the first preset threshold and less than the second preset threshold.

The image enhancement apparatus provided in this embodiment can be used to perform the method of the embodiment of FIG. 2, and the execution manner and the beneficial effects are similar, and details are not described herein again.

6 is a schematic structural diagram of an image enhancement apparatus according to an embodiment of the present disclosure. As shown in FIG. 6, on the basis of the embodiment of FIG. 4, the brightness characteristic of the target image includes respective areas of different areas on the target image. The average brightness; the processing module 43 includes:

a first processing sub-module 431, configured to perform image enhancement processing on the region based on a target image enhancement algorithm that is adapted to an average brightness of the region for different regions on the target image;

or

The second processing sub-module 432 is configured to repeatedly perform image enhancement processing on the target image as a whole based on a plurality of target image enhancement algorithms respectively corresponding to different regions on the target image.

The image enhancement apparatus provided in this embodiment can be used to perform the method of the embodiment of FIG. 3, and the execution manner and the beneficial effects are similar, and details are not described herein again.

FIG. 7 is a schematic structural diagram of a terminal device according to an embodiment of the present disclosure. The terminal device may be, for example, a mobile terminal such as a mobile phone, or may be a traffic camera or the like. As shown in FIG. 7, a terminal device 700 includes:

Processor 701;

a memory 702, configured to store computer executable instructions and image data;

When the processor executes the computer executable instructions, the technical solution of the above method embodiments can be implemented.

The embodiment of the present disclosure further provides a computer readable non-volatile storage medium, including computer instructions, which can implement the technical solutions of the foregoing method embodiments when the computer instructions are run on a processor.

Finally, it should be understood that those skilled in the art can understand that all or part of the processes in the above embodiment methods can be completed by a computer program to instruct related hardware, and the program can be stored in a computer readable storage medium. The program, when executed, may include the flow of an embodiment of the methods as described above. The storage medium may be a magnetic disk, an optical disk, a read only memory (ROM), or a random access memory (RAM).

The various functional units in the embodiments of the present disclosure may be integrated into one processing module, or may be physically separated by individual units, or two or more units may be integrated into one module. The above integrated modules can be implemented in the form of hardware or in the form of software functional modules. The integrated modules, if implemented in the form of software functional modules and sold or used as separate products, may also be stored in a computer readable storage medium. The storage medium mentioned above may be a read only memory, a magnetic disk or an optical disk or the like.

The above embodiments are only for explaining the technical solutions of the present disclosure, and are not intended to be limiting thereof; although the present disclosure has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art will understand that The technical solutions described in the examples are modified, or some or all of the technical features are equivalently substituted; and the modifications or substitutions do not deviate from the scope of the technical solutions of the embodiments of the present disclosure.

Claims (12)

An image enhancement method comprising: Defogging the first image to obtain a target image; Determining, from a plurality of preset image enhancement algorithms, a target image enhancement algorithm that is adapted to the brightness characteristics of the target image based on a preset strategy; Image enhancement processing is performed on the target image based on the target image enhancement algorithm. The method according to claim 1, wherein the plurality of preset image enhancement algorithms comprise: a plurality of linear transformation algorithms, automatic transformation algorithms, log transformation algorithms, and gamma transformation algorithms. The method according to claim 2, wherein the brightness characteristic of the target image comprises an average brightness of the target image as a whole; Determining, according to a preset strategy, a target image enhancement algorithm that is adapted to the brightness feature of the target image from a plurality of preset image enhancement algorithms, including: If the average brightness of the target image as a whole is less than a first preset threshold, determining that the automatic transform algorithm is a target image enhancement algorithm; And if the average brightness of the target image as a whole is greater than the first preset threshold and less than the second preset threshold, determining that the logarithmic transformation algorithm or the gamma transformation algorithm is the target image enhancement algorithm. The method according to claim 1, wherein the brightness characteristic of the target image comprises respective average brightness of different regions on the target image; And performing image enhancement processing on the target image based on the target image enhancement algorithm, including: An image enhancement process is performed on the region based on a target image enhancement algorithm that is adapted to the average brightness of the region for different regions on the target image. The method according to claim 1, wherein the brightness characteristic of the target image comprises respective average brightness of different regions on the target image; And performing image enhancement processing on the target image based on the target image enhancement algorithm, including: The image enhancement processing is repeatedly performed on the target image as a whole based on a plurality of target image enhancement algorithms respectively corresponding to different regions on the target image. An image enhancement device comprising: a defogging module, configured to perform a defogging process on the first image to obtain a target image; a determining module, configured to determine, according to a preset policy, a target image enhancement algorithm that is adapted to a brightness feature of the target image from among a plurality of preset image enhancement algorithms; And a processing module, configured to perform image enhancement processing on the target image based on the target image enhancement algorithm. The apparatus according to claim 6, wherein the plurality of preset image enhancement algorithms comprise: a linear transformation algorithm, an automatic transformation algorithm, a logarithmic transformation algorithm, and a gamma transformation algorithm. The apparatus according to claim 7, wherein the brightness characteristic of the target image comprises an average brightness of the entire target image; The determining module includes: a first determining submodule, configured to determine that the automatic transform algorithm is a target image enhancement algorithm when an average brightness of the target image as a whole is less than a first preset threshold; The second determining submodule is configured to determine that the logarithmic transform algorithm or the gamma transform algorithm is the target image enhancement algorithm when the average brightness of the target image as a whole is greater than the first preset threshold and less than the second preset threshold. The apparatus according to claim 6, wherein the brightness characteristic of the target image comprises respective average brightness of different areas on the target image; The processing module includes: And a first processing submodule, configured to perform image enhancement processing on the region based on a target image enhancement algorithm that is adapted to an average brightness of the region for different regions on the target image. The apparatus according to claim 6, wherein the brightness characteristic of the target image comprises respective average brightness of different areas on the target image; The processing module includes: a second processing submodule, configured to repeatedly perform image enhancement processing on the target image as a whole based on a plurality of target image enhancement algorithms respectively corresponding to different regions on the target image. A terminal device comprising: processor; a memory for storing computer executable instructions; The method of any of the preceding claims 1-5, when the computer executable instructions are executed by the processor. A computer readable non-volatile storage medium having stored thereon computer instructions that, when executed by a processor, implement the method of claims 1 to 5.

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