CN113837951A - Image brightness improving method and device, data processing equipment and storage medium - Google Patents
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Abstract
The application provides an image brightness improving method, an image brightness improving device, a data processing device and a storage medium. The brightness of part of target pixels in the target image is improved by a non-linear function in which the change rate of the function result is reduced along with the increase of the brightness in a preset brightness range. Since the rate of change of the function result of the non-linear function decreases with increasing brightness, the pixels with larger brightness do not change too much significantly due to the non-linear function. Meanwhile, the brightness of part of target pixels in the target image is selectively adjusted. Therefore, overexposure and lack of gradation can be reduced.
Description
Technical Field
The present application relates to the field of data processing, and in particular, to a method and an apparatus for improving image brightness, a data processing device, and a storage medium.
Background
In order to improve the visual effect of an image, it is necessary to enhance the brightness of the image so that the processed image has a whitening effect. However, the image processed by the conventional image brightness enhancement method may have problems such as overexposure and lack of gradation.
Disclosure of Invention
To overcome at least one of the deficiencies in the prior art, an object of the embodiments of the present application is to provide an image brightness improving method applied to a data processing device, the method including:
acquiring a target image to be processed;
determining at least one part of pixels from the target image as target pixels;
and improving the brightness of the target pixel through a nonlinear function to obtain a processed target image, wherein the higher the brightness of the target pixel is, the smaller the improvement degree of the brightness of the target pixel by the nonlinear function is.
Optionally, the step of determining at least a part of pixels from the target image as target pixels includes:
and for each pixel in the target image, comparing the brightness of the pixel with a reference brightness, and determining the pixel with the brightness smaller than the reference brightness as the target pixel.
Optionally, before comparing the brightness of the pixel with the reference brightness, the method further includes:
and counting the average brightness of each pixel in the target image, and taking the average brightness as the reference brightness.
Optionally, the data processing device comprises a central processor and an image processor;
the step of counting the average brightness of each pixel in the target image and using the average brightness as the reference brightness includes:
counting the average brightness of each pixel in the target image through the central processing unit, and taking the average brightness as the reference brightness;
the step of increasing the brightness of at least a part of target pixels in the target image through a nonlinear function to obtain processed target pixels includes:
and improving the brightness of the target pixel in the target image according to the nonlinear function by the image processor to obtain the processed target pixel.
Optionally, the data processing device prestores a first ambient brightness when a reference image is acquired, the target image is a current image in a live video, and before comparing the brightness of the pixel with the reference brightness, the method further includes:
acquiring second ambient brightness when the image to be processed is acquired, wherein the appearance time of the reference image in the live video is earlier than that of the image to be processed in the live video;
calculating a brightness difference between the first ambient brightness and the second ambient brightness;
if the brightness difference exceeds a brightness threshold, taking the image to be processed as a new reference image;
and counting the average brightness of each pixel in the new reference image, and taking the average brightness of each pixel in the new reference image as the reference brightness.
Optionally, before comparing the brightness of the pixel with the reference brightness, the method further includes:
and responding to a first input operation, and obtaining the input reference brightness.
Optionally, the luminance of the target pixel is determined by the RGB value of the target pixel, and the non-linear function is a quadratic function based on S, where S is a color parameter selected from the RGB value of the target pixel.
Optionally, the expression of the quadratic function is:
in the formula, T is the processed color parameter, e is a brightening factor for the user to adjust, and the value range of the brightening factor is 0 to 1.
Optionally, the method further comprises:
and responding to a second input operation, and obtaining the input brightness factor.
Optionally, the method further comprises:
responding to a third input operation, taking the ratio of the processed color parameter to 255 as an iteration initial value, and iterating through the following expression:
Mn+1＝Mn+D-Mn*D；
where n is the number of iterations, D is the ratio of the color parameter selected from the RGB values of the target pixel to 255, the selected color parameter corresponding to the processed color parameter, and M is the ratio of the color parameter to 255n+1Is the ratio after iteration;
and multiplying the iterated ratio by 255 to obtain an iterated color parameter value.
It is another object of an applied embodiment to provide an image brightness improving apparatus applied to a data processing device, the image brightness improving apparatus including:
the image acquisition module is used for acquiring a target image;
the brightness improving module is used for improving the brightness of at least one part of target pixels in the target image through a nonlinear function to obtain processed target pixels, wherein the nonlinear function is in a preset brightness range, and the change rate of a function result is reduced along with the increase of the brightness;
and the target acquisition module is used for acquiring a processed target image according to the processed target pixel.
Optionally, the data processing device comprises a processor and a memory, wherein the memory stores machine executable instructions capable of being executed by the processor, and when the machine executable instructions are executed by the processor, the method for improving the brightness of the image is realized.
Optionally, the storage medium stores a computer program, and the computer program, when executed by a processor, implements the image brightness improving method.
Compared with the prior art, the method has the following beneficial effects:
the embodiment of the application provides a method and a device for improving image brightness, data processing equipment and a storage medium. The brightness of part of target pixels in the target image is improved by a non-linear function in which the change rate of the function result is reduced along with the increase of the brightness in a preset brightness range. Since the rate of change of the function result of the non-linear function decreases with increasing brightness, the pixels with larger brightness do not change too much significantly due to the non-linear function. Meanwhile, the brightness of part of target pixels in the target image is selectively adjusted. Therefore, overexposure and lack of gradation can be reduced.
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In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.
Fig. 1 is a schematic hardware structure diagram of a data processing device according to an embodiment of the present application;
FIG. 2 is a flowchart illustrating steps of a method for enhancing image brightness according to an embodiment of the present disclosure;
FIG. 3 is a schematic diagram of a step of calculating average luminance according to an embodiment of the present disclosure;
fig. 4 is a schematic structural diagram of an image brightness improving apparatus according to an embodiment of the present application.
Icon: 110-image brightness enhancing means; 120-a memory; 130-a processor; 1101-an image acquisition module; 1102-a pixel determination module; 1103-brightness enhancement module.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
In the description of the present application, it is noted that the terms "first", "second", "third", and the like are used merely for distinguishing between descriptions and are not intended to indicate or imply relative importance.
As described in the background art, in order to improve the visual effect of an image, it is necessary to perform enhancement processing on the brightness of the image so that the processed image exhibits a whitening effect. However, the image processed by the conventional image brightness enhancement method may have problems such as overexposure and lack of gradation.
In view of this, the present application provides an image brightness improving method, which is applied to a data processing device. Referring to fig. 1, a schematic diagram of a hardware structure of the data processing apparatus according to the embodiment of the present application is shown.
The data processing apparatus includes an image brightness enhancing device 110, a memory 120, and a processor 130. The memory 120 and the processor 130 are directly or indirectly communicatively coupled to each other to enable data transfer or interaction. For example, the components may be electrically connected to each other via one or more communication buses or signal lines. The image brightness enhancing device 110 includes at least one software functional module which can be stored in the memory 120 in the form of software or Firmware (Firmware) or solidified in an Operating System (OS) of the data processing apparatus. The processor 130 is used for executing executable modules stored in the memory 120, such as software functional modules and computer programs included in the image brightness enhancing apparatus 110.
The Memory 120 may be, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Read-Only Memory (EPROM), an electrically Erasable Read-Only Memory (EEPROM), and the like. The memory 120 is used for storing a program, and the processor 130 executes the program after receiving the execution instruction.
The Memory 120 may be, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Read-Only Memory (EPROM), an electrically Erasable Read-Only Memory (EEPROM), and the like. The memory 120 is used for storing a program, and the processor 130 executes the program after receiving the execution instruction. Access to the memory 120 by the processor 130 and possibly other components may be under the control of the memory controller.
The processor 130 may be an integrated circuit chip having signal processing capabilities. The Processor may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; but may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. The various methods, steps, and logic blocks disclosed in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
Referring to fig. 2, a flowchart of an image brightness improving method applied to the data processing apparatus shown in fig. 1 according to an embodiment of the present application is shown, and the method including various steps will be described in detail below.
Step S100, a target image is acquired.
In step S200, at least a part of pixels are determined from the target image as target pixels.
And step S300, improving the brightness of the target pixel through a nonlinear function to obtain a processed target image, wherein the higher the brightness of the target pixel is, the smaller the improvement degree of the brightness of the target pixel by the nonlinear function is.
It should be understood that, for different image coding modes, there is a certain difference in the parameters reflecting the pixel brightness in the image.
Taking an RGB-encoded image as an example, each pixel in the image includes three parameters, RGB. The three parameters RGB collectively reflect the luminance of the pixel, i.e. the larger the value of the three parameters RGB is, the closer the color of the pixel is to white, and the higher the luminance of the corresponding pixel is.
Similarly, in the image coded in the YUV mode, each pixel in the image comprises three YUV parameters. Wherein the parameter Y is used for determining the brightness of the pixel.
In the image brightness improving method, the brightness of part of target pixels in a target image is improved through a nonlinear function in which the change rate of a function result is reduced along with the increase of the brightness in a preset brightness range. Since the rate of change of the function result of the non-linear function decreases with increasing brightness, the pixels with larger brightness do not change too much significantly due to the non-linear function. Meanwhile, the brightness of part of target pixels in the target image is selectively adjusted. Therefore, overexposure and lack of gradation can be reduced.
In order to avoid performing brightness enhancement on pixels whose brightness has reached a certain degree, the data processing device compares, for each pixel in the target image, the brightness of the pixel with a reference brightness, and determines a pixel whose brightness is less than the reference brightness as the target pixel.
Because the pixels in the image are screened by referring to the brightness, the situation that the brightness of the pixels with the brightness reaching a certain degree is enhanced again and then the overexposure phenomenon occurs can be avoided. Meanwhile, compared with the method that the brightness of a certain area in the target image is only improved, the target image is screened in the global scope through the reference brightness, and the brightness of the processed target image is more uniform.
As a possible embodiment, the data processing device counts an average luminance of each pixel in the target image with respect to the reference luminance, and takes the average luminance as the reference luminance. Of course, the average brightness may be adjusted appropriately based on the average brightness, and the embodiment of the present application is not limited to this.
For example, for a target image encoded in RGB system, the average luminance of the target image can be calculated as follows:
where i denotes the ith pixel in the target image, ri、giAnd biRespectively representing RGB values, L, of the ith pixeliIndicating the luminance value of the ith pixel. Further, the average brightness of the target image may be expressed as:
in the formula, LbRepresenting the average luminance of the processed image and N represents all pixels in the target image.
As another possible embodiment, the data processing apparatus provides an input interface for the reference brightness, and obtains the reference brightness in response to a first input operation in the input interface. Of course, the data processing device may also provide the average brightness of the target image for reference by the user. More operation space can be provided for the user through the input interface.
In addition, in one possible application scenario, the target image is a current image in a live video. In a live scene, the anchor needs to improve the brightness of a live picture in order to achieve a better viewing effect. When the live broadcast is carried out outdoors, the brightness of a live broadcast picture changes along with the change of the position of the main broadcast. Although the average brightness is calculated for each frame of image, the real-time performance in the process of adjusting the brightness of the picture can be improved, but the method occupies excessive computing resources.
In view of this, referring to fig. 3, in a live scene, the data processing device prestores a first ambient brightness when capturing a reference image, the target image is a current image in a live video, and the data processing device determines the reference brightness by:
and S500, acquiring second ambient brightness when the image to be processed is acquired, wherein the appearance time of the reference image in the live video is earlier than that of the image to be processed in the live video.
In step S600, a luminance difference between the first ambient luminance and the second ambient luminance is calculated.
In step S700, if the brightness difference exceeds the brightness threshold, the image to be processed is taken as a new reference image.
Step S800, counting the average brightness of each pixel in the new reference image, and using the average brightness of each pixel in the new reference image as the reference brightness.
It should be understood that the data processing device may detect the brightness in the live environment through the light sensor, and when the brightness change exceeds a set brightness threshold, a large change in the live environment is indicated. I.e. the anchor may move from a place where the intensity is stronger to a place where the intensity is weaker, or the anchor may move from a place where the intensity is weaker to a place where the intensity is stronger.
Taking a live video as an example, since the data processing device prestores a first ambient brightness when a reference image is captured, when a change of a second ambient brightness of the data processing device at time t compared with the first ambient brightness exceeds a brightness threshold, taking a current image of the live video at time t as a new reference image, counting an average brightness of each pixel in the new reference image, and taking an average brightness of each pixel in the new reference image as a reference brightness. And determining the target pixel by the reference brightness of the images after the time t of the live video until the brightness change in the environment exceeds the brightness threshold again, and re-determining the new reference brightness.
The reference brightness can be modified along with the change of the environment where the anchor is located, and the average brightness does not need to be calculated for each frame of image, so that the adaptability to different environments is improved, and certain calculation resources can be saved.
Wherein, as a possible implementation manner, the non-linear function is a quadratic function based on S, where S is a color parameter selected from the RGB values of the target pixel, and the luminance of the target pixel is determined by the RGB values of the target pixel.
For the quadratic function, the expression of the quadratic function may be:
in the formula, T is the processed color parameter, e is a brightening factor for the user to adjust, and the value range of the brightening factor is 0 to 1. The brightness enhancement effect on the target image is changed due to the fact that the brightness enhancement factor can change the shape of the nonlinear function to a certain extent. Therefore, by providing the brightness enhancement factor, the user is enabled to fine-tune the brightness of the target image within a small range.
The expression for this non-linear function can be converted to the following form:
that is, after normalization processing is performed on each RGB value by 255, the RGB values will be normalized
And is indicated as y, in the figure,
expressed as a, the expression of the non-linear function can be converted intoThe following forms:
y＝2a-ea2；
wherein, since e is a brightening factor for self-adjustment of the user, when e is determined, the function y is 2a-ea2A quadratic function with a decreasing slope with a increasing function slope and approaching 0 as the maximum value of the function is approached.
Further, since the adjustment range of the target image by the brightening factor is small, the data processing apparatus may further iterate by using the ratio of the processed color parameter to 255 as an iteration initial value in response to a third operation input by the user, by using the following expression:
Mn+1＝Mn+D-Mn*D；
where n is the number of iterations and D is the ratio of the color parameter selected from the RGB values of the target pixel to 255. The selected color parameter corresponds to the processed color parameter, that is, the processed color parameter and the selected color parameter are directed to the same color in the target pixel. Mn+1Is the ratio after iteration;
the data processing device multiplies the iterated ratio by 255 to obtain iterated color parameter values.
When the target image is processed, the calculation amount of the target image is positively correlated with the resolution of the target image. In order to improve the efficiency when the brightness of the target image is enhanced, the data processing device includes a central processing unit and an image processor. The data processing equipment counts the average brightness of each pixel in the target image through the central processing unit, and takes the average brightness as the reference brightness; and improving the brightness of the target pixel in the target image according to the nonlinear function by the image processor to obtain the processed target pixel.
Since the image processor can perform parallel processing on each pixel of the target image, it is possible to improve the efficiency when performing brightness enhancement on the band-processed image. Especially, when live broadcasting, the delay of live broadcasting pictures can be reduced, and the user experience is improved.
Referring to fig. 4, an image brightness improving apparatus 110, an application and a data processing device are also provided in the present embodiment. The image brightness enhancing apparatus 110 includes at least one functional module that can be stored in the memory 120 in the form of software. Functionally, the image brightness enhancing apparatus 110 may include:
an image acquisition module 1101 is configured to acquire a target image.
In the embodiment of the present application, the image acquisition module 1101 is configured to perform step S100 in fig. 2, and as to the detailed description of the image acquisition module 1101, reference may be made to the detailed description of step S100.
A pixel determining module 1102, configured to determine at least a portion of pixels from the target image as target pixels.
In the embodiment of the present application, the pixel determining module 1102 is configured to execute step S200 in fig. 2, and as to the detailed description of step S200, refer to the detailed description of step S200.
The brightness improving module 1103 is configured to obtain a processed target image according to the processed target pixel.
In the embodiment of the present application, the brightness increasing module 1103 is configured to execute step S300 in fig. 2, and as to the detailed description of step S300, reference may be made to the detailed description of step S300.
The embodiment of the present application further provides a data processing device, which includes a processor 130 and a memory 120, where the memory 120 stores machine executable instructions capable of being executed by the processor 130, and when the machine executable instructions are executed by the processor 130, the method for improving image brightness is implemented.
The embodiment of the present application further provides a storage medium, where a computer program is stored, and when the computer program is executed by the processor 130, the method for improving the brightness of the image is implemented.
In summary, the image brightness improving method and apparatus, the data processing device, and the storage medium provided in the embodiments of the present application are provided. The brightness of part of target pixels in the target image is improved by a non-linear function in which the change rate of the function result is reduced along with the increase of the brightness in a preset brightness range. Since the rate of change of the function result of the non-linear function decreases with increasing brightness, the pixels with larger brightness do not change too much significantly due to the non-linear function. Meanwhile, the brightness of part of target pixels in the target image is selectively adjusted. Therefore, overexposure and lack of gradation can be reduced.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The apparatus embodiments described above are merely illustrative, and for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The above description is only for various embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of changes or substitutions within the technical scope of the present application, and all such changes or substitutions are included in the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (13)
1. An image brightness improvement method applied to a data processing device, the method comprising:
acquiring a target image to be processed;
determining at least one part of pixels from the target image as target pixels;
and increasing the brightness of the target pixel through a nonlinear function to obtain a processed target image, wherein the higher the brightness of the target pixel is, the smaller the increase degree of the brightness of the target pixel is.
2. The method according to claim 1, wherein the step of determining at least a part of pixels from the target image as target pixels comprises:
and for each pixel in the target image, comparing the brightness of the pixel with a reference brightness, and determining the pixel with the brightness smaller than the reference brightness as the target pixel.
3. The method of claim 2, wherein before comparing the brightness of the pixel with the reference brightness, the method further comprises:
and counting the average brightness of each pixel in the target image, and taking the average brightness as the reference brightness.
4. The method according to claim 3, wherein the data processing device comprises a central processing unit and an image processor;
the step of counting the average brightness of each pixel in the target image and using the average brightness as the reference brightness includes:
counting the average brightness of each pixel in the target image through the central processing unit, and taking the average brightness as the reference brightness;
the step of increasing the brightness of at least a part of target pixels in the target image through a nonlinear function to obtain processed target pixels includes:
and improving the brightness of the target pixel in the target image according to the nonlinear function by the image processor to obtain the processed target pixel.
5. The method according to claim 2, wherein the data processing device prestores a first ambient brightness when capturing a reference image, the target image is a current image in a live video, and before comparing the brightness of the pixel with the reference brightness, the method further comprises:
acquiring second ambient brightness when the image to be processed is acquired, wherein the appearance time of the reference image in the live video is earlier than that of the image to be processed in the live video;
calculating a brightness difference between the first ambient brightness and the second ambient brightness;
if the brightness difference exceeds a brightness threshold, taking the image to be processed as a new reference image;
and counting the average brightness of each pixel in the new reference image, and taking the average brightness of each pixel in the new reference image as the reference brightness.
6. The method of claim 2, wherein before comparing the brightness of the pixel with the reference brightness, the method further comprises:
and responding to a first input operation, and obtaining the input reference brightness.
7. The method as claimed in claim 1, wherein the luminance of the target pixel is determined by RGB values of the target pixel, and the non-linear function is a quadratic function based on S, wherein S is a color parameter selected from the RGB values of the target pixel.
8. The image luminance improvement method according to claim 7, wherein the expression of the quadratic function is:
in the formula, T is the processed color parameter, e is a brightening factor for the user to adjust, and the value range of the brightening factor is 0 to 1.
9. The method for improving image brightness according to claim 8, further comprising:
and responding to a second input operation, and obtaining the input brightness factor.
10. The method for improving image brightness according to claim 8, further comprising:
responding to a third input operation, taking the ratio of the processed color parameter to 255 as an iteration initial value, and iterating through the following expression:
Mn+1＝Mn+D-Mn*D；
where n is the number of iterations, D is the ratio of the color parameter selected from the RGB values of the target pixel to 255, the selected color parameter corresponding to the processed color parameter, and M is the ratio of the color parameter to 255n+1Is the ratio after iteration;
and multiplying the iterated ratio by 255 to obtain an iterated color parameter value.
11. An image brightness improving apparatus applied to a data processing device, the image brightness improving apparatus comprising:
the image acquisition module is used for acquiring a target image;
the brightness improving module is used for improving the brightness of at least one part of target pixels in the target image through a nonlinear function to obtain processed target pixels, wherein the nonlinear function is in a preset brightness range, and the change rate of a function result is reduced along with the increase of the brightness;
and the target acquisition module is used for acquiring a processed target image according to the processed target pixel.
12. A data processing apparatus comprising a processor and a memory, said memory storing machine executable instructions executable by said processor, said machine executable instructions when executed by said processor implementing the method of image brightness enhancement according to any one of claims 1 to 10.
13. A storage medium, characterized in that the storage medium stores a computer program which, when executed by a processor, implements the image brightness improvement method according to any one of claims 1 to 10.
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