Display image acquisition method and device, computer equipment and storage medium

Abstract

The invention discloses a display image acquisition method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring a standard gray scale test image; performing image content processing on the standard gray scale test image to obtain a first processing image; performing image display effect calibration processing on the first processing image to obtain a second processing image; establishing a mapping relation between the first processing image and the second processing image, and generating a mapping table; collecting a target image after image content processing and image display effect calibration processing; and performing gray scale redirection on the target image by using the generated mapping table to obtain image information of the target image before image display effect calibration processing. By establishing the mapping table of the standard gray scale test image and then performing gray scale redirection on the input target image according to the mapping table, image information without image display effect calibration processing is obtained, so that problems related to image processing are analyzed more truly.

Description

Technical Field

[0001] The present invention relates to the field of display technology, and more specifically to a display image acquisition method, device, computer equipment and storage medium. Background Art

[0002] With the large-scale use of AI technology and various image processing technologies, the image display effect has made a qualitative leap. Different display devices have different image processing technologies, especially the use of AI technology, which has greatly improved the brightness, contrast and structure related to image quality. In addition, different displays have processing such as GAMMA, color temperature and color gamut correction. This makes the same image source present different styles of display effects on different display devices, resulting in the original real processing result of the image being obtained from the display, that is, it is difficult to get what the image looked like before processing such as GAMMA, color temperature and color gamut correction. This has a huge impact on the evaluation of the image effect of the display device and the data source collection of the original processed image effect for the AI ​​training model.

[0003] Therefore, it is necessary to design a method that can remove the interference factors such as GAMMA, color temperature, and color gamut correction to obtain the real image information after image processing, which is an urgent problem to be solved. Summary of the invention

[0004] The purpose of the present invention is to overcome the deficiencies of the prior art and to provide a display image acquisition method, device, computer equipment and storage medium.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] The present invention provides a display image acquisition method, comprising:

[0007] Obtain a standard grayscale test image;

[0008] Performing image content processing on the standard grayscale test image to obtain a first processed image;

[0009] Performing image display effect calibration processing on the first processed image to obtain a second processed image;

[0010] Establishing a mapping relationship between the first processed image and the second processed image, and generating a mapping table;

[0011] Acquire the target image after image content processing and image display effect calibration;

[0012] The generated mapping table is used to perform grayscale redirection on the target image to obtain image information of the target image before image display effect calibration processing.

[0013] Furthermore, the standard grayscale test image is an image with 8-bit signal characteristics and covers a continuous transition from 0 to 255 grayscales.

[0014] Furthermore, the image content processing includes at least one of the following: brightness adjustment, contrast adjustment and AI processing.

[0015] Furthermore, the image display effect calibration process includes at least one of the following: GAMMA correction process, color temperature correction process and color gamut correction process.

[0016] Further, the establishing a mapping relationship between the first processed image and the second processed image and generating a mapping table includes:

[0017] dividing the first processed image into a plurality of pixel regions;

[0018] Recording the original grayscale values ​​of all color channels in each pixel area in the first processed image;

[0019] Recording updated grayscale values ​​of all color channels in the same pixel region in the second processed image as in the first processed image;

[0020] The correspondence between the original grayscale values ​​and the updated grayscale values ​​of all color channels in all pixel regions is counted to construct a mapping table.

[0021] Furthermore, the pixel area is a set of one or more gray levels.

[0022] Furthermore, the grayscale redirection of the target image using the generated mapping table to obtain image information of the target image before the image display effect calibration process is performed includes:

[0023] Obtain the grayscale feature information of all color channels in each pixel area in the target image;

[0024] Find the original grayscale value corresponding to the grayscale feature information extracted from the current pixel area in the mapping table;

[0025] Restore the current grayscale values ​​of all color channels of each pixel area to the original grayscale values.

[0026] In a second aspect, the present invention further provides a display image acquisition device, comprising:

[0027] An acquisition unit, used for acquiring a standard grayscale test image;

[0028] A first image processing unit, configured to perform image content processing on a standard grayscale test image to obtain a first processed image;

[0029] A second image processing unit, used for performing image display effect calibration processing on the first processed image to obtain a second processed image;

[0030] A mapping table building unit, used to establish a mapping relationship between the first processed image and the second processed image, and generate a mapping table;

[0031] An acquisition unit, used for acquiring a target image after image content processing and image display effect calibration processing;

[0032] The grayscale redirection unit is used to perform grayscale redirection on the target image using the generated mapping table to obtain image information of the target image before image display effect calibration processing.

[0033] In a third aspect, the present invention further provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the display image acquisition method as described above when executing the computer program.

[0034] In a fourth aspect, the present invention further provides a computer-readable storage medium, wherein the storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a processor, the processor executes the display image acquisition method as described above.

[0035] Compared with the prior art, the present invention has the following beneficial effects: a display image acquisition method, comprising: obtaining a standard grayscale test image; performing image content processing on the standard grayscale test image to obtain a first processed image; performing image display effect calibration processing on the first processed image to obtain a second processed image; establishing a mapping relationship between the first processed image and the second processed image, and generating a mapping table; acquiring a target image after image content processing and image display effect calibration processing; performing grayscale redirection on the target image using the generated mapping table to obtain image information of the target image before image display effect calibration processing. The present invention completes the data acquisition work by establishing a mapping table of a standard grayscale test image, and then performing grayscale redirection on the input target image according to the mapping table to obtain image information without image display effect calibration processing, so as to more realistically analyze problems related to image processing.

[0036] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the following preferred embodiments are specifically cited and described in detail as follows. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying any creative work.

[0038] Figure 1 A flowchart of a display image acquisition method provided by a specific embodiment of the present invention;

[0039] Figure 2 A schematic block diagram of a display image acquisition device provided in a specific embodiment of the present invention;

[0040] Figure 3 A schematic block diagram of a computer device provided for a specific embodiment of the present invention. DETAILED DESCRIPTION

[0041] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0042] It should be understood that when used in this specification and the appended claims, the terms "include" and "comprises" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0043] It should also be understood that the terms used in the present specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0044] It should be further understood that the term "and / or" used in the present description and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0045] like Figure 1 As shown, an embodiment of the present invention provides a display image acquisition method, including the following steps: S10-S60.

[0046] S10, obtaining a standard grayscale test image.

[0047] The standard grayscale test image has 8-bit signal characteristics and covers a continuous transition from 0 to 255 grayscales. That is, it uses 8-bit binary encoding (8bit) to represent the grayscale information of pixels. This means that the grayscale value of each pixel can be represented by an 8-bit binary number, with a value range of 0 (corresponding to binary 00000000, indicating pure black) to 255 (corresponding to binary 11111111, indicating pure white), forming a complete grayscale system with a continuous transition from black to white.

[0048] S20: performing image content processing on the standard grayscale test image to obtain a first processed image.

[0049] Image content processing is mainly used to improve image display quality or apply specific display technologies. For example, the display may use internal algorithms to increase image brightness, improve contrast, sharpen image structure, or apply AI technology to optimize certain details of the image. These processes are intended to make the image more visually attractive or meet specific display requirements.

[0050] In this embodiment, the image content processing includes at least one of the following: brightness adjustment, contrast adjustment and AI processing.

[0051] Specifically, brightness adjustment: the image is processed according to the preset brightness gain value through the brightness control module built into the display image processing chip. For example, when the overall brightness of the image needs to be increased to observe the dark details, the brightness gain is set to 0.2, and the grayscale value of each pixel in the image is calculated and updated according to the formula: new grayscale value = original grayscale value * (1 + brightness gain). If the grayscale value of a pixel in the original image is 50, after brightness adjustment, the new grayscale value becomes 50*(1+0.2)=60.

[0052] Contrast adjustment: Contrast enhancement algorithm is used, which automatically identifies bright and dark areas by analyzing the distribution of grayscale in the image. For bright areas, the upper limit of grayscale value is increased by a certain proportion, such as increasing by 20%; for dark areas, the lower limit of grayscale value is reduced, such as reducing by 15%. The bright areas are brighter, the dark areas are darker, and the image details are more prominent. For example, for a landscape image, the grayscale value of the sky part (bright part) was originally between 180-220, and after contrast adjustment, the grayscale value becomes between 216-264; and the grayscale value of the ground shadow part (dark part) was originally between 30-60, and after adjustment, it becomes between 25-51.

[0053] AI processing: Using a pre-trained deep learning model, the model is trained based on a large amount of different types of image data and can recognize various patterns and features in the image. When applied to a standard grayscale test image, it can intelligently adjust the grayscale value of the local area according to the overall grayscale distribution trend of the image, making the grayscale transition more natural and smooth. For example, if the model detects that there is an area in the image where the grayscale value suddenly jumps from 100 to 150, and there is a lack of transition in the middle, it will automatically insert some intermediate grayscale values ​​between these two values, such as 110, 120, 130, 140, so that the grayscale change looks more continuous and optimizes the image visual effect.

[0054] S30: Perform image display effect calibration processing on the first processed image to obtain a second processed image.

[0055] The purpose of image display calibration is to make the display output meet certain color standards or maintain relatively stable and accurate color display in different environments. For example, GAMMA calibration is used to adjust the nonlinear relationship between image brightness and contrast, color temperature calibration ensures that white looks like true white (rather than warm or cold tones), and color gamut calibration enables the display to accurately display colors in a specific color range.

[0056] In this embodiment, the image display effect calibration process includes at least one of the following: a GAMMA correction process, a color temperature correction process, and a color gamut correction process.

[0057] Specifically, GAMMA correction processing: The GAMMA correction circuit of the display performs nonlinear transformation on the grayscale value of each pixel in the first processed image according to the internationally accepted GAMMA standard curve (such as the common 2.2 or 2.4 curve). Specifically, for pixels with lower grayscale values, they are stretched according to the low grayscale part of the curve so that they can display rich details even in low-brightness environments; for pixels with higher grayscale values, they are compressed according to the high grayscale part of the curve to prevent overexposure of brightness. For example, using a 2.2 GAMMA curve, when the input grayscale value is 30, the corrected output grayscale value may become 45; when the input grayscale value is 200, the output grayscale value may become 180.

[0058] Color temperature correction processing: The color temperature of the ambient light is monitored in real time through the color temperature sensor, and then the color temperature parameters of the display are adjusted according to the monitoring results. If the ambient light is warm (low color temperature, such as 3000K), the display will automatically increase the gain of the blue channel and reduce the gain of the red and green channels, so that the displayed white looks closer to the standard white (color temperature 6500K). Conversely, if the ambient light is cold (higher color temperature, such as 8000K), the gain of the red and green channels is increased, and the gain of the blue channel is reduced. Taking the indoor yellow light environment as an example, the display detects that the ambient color temperature is 3500K, and then adjusts the image red channel gain to 0.9, the green channel gain to 0.9, and the blue channel gain to 1.2 to ensure that the image color is not affected by the color temperature of the ambient light.

[0059] Color gamut correction processing: With the help of the built-in color gamut calibration module, the color gamut range currently supported by the display (such as sRGB, Adobe RGB, etc.) is compared with the standard color gamut range, and the colors in the image that exceed or do not reach the standard color gamut are adjusted. If the coordinates of a color in the image are outside the standard color gamut, it is mapped to the color coordinates in the closest standard color gamut through the color space conversion algorithm. For example, for a bright purple, its color gamut coordinates before calibration exceed the sRGB standard color gamut. After color gamut correction, it is mapped to the purple coordinates in the sRGB color gamut that are closest to its visual effect, ensuring the accuracy and consistency of the image color.

[0060] S40: Establish a mapping relationship between the first processed image and the second processed image, and generate a mapping table.

[0061] In one embodiment, step S40 specifically includes the following steps: S401 - S404 .

[0062] S401: Divide a first processed image into a plurality of pixel regions.

[0063] The image can be divided into 100×100 square grids of equal size according to the resolution and required accuracy of the image, and each square grid area is used as a basic analysis unit. It can also be divided according to the content characteristics of the image, such as for portrait images, adaptive division is performed according to different areas such as face, hair, and clothes, ensuring that the division is finer in the grayscale change sensitive area and relatively rough in the relatively uniform area, thereby improving the efficiency and accuracy of establishing the mapping relationship.

[0064] It should be noted that the pixel area is a set of one or more gray levels. In this embodiment, the pixel area is one gray level.

[0065] S402, recording original grayscale values ​​of all color channels in each pixel area in the first processed image.

[0066] For each divided pixel area, use image analysis software or hardware module to extract the grayscale values ​​of the three color channels of red (R), green (G), and blue (B). For example, in a square area in the upper left corner, the grayscale value of the red channel is 80, the grayscale value of the green channel is 90, and the grayscale value of the blue channel is 70. These values ​​are recorded as the original grayscale values.

[0067] S403, recording updated grayscale values ​​of all color channels in the same pixel region in the second processed image as that in the first processed image.

[0068] Similarly, for the second processed image, find the grid area corresponding to the first processed image, and use the high-precision acquisition device again to read the grayscale values ​​of the three color channels in the area. Due to the image display effect calibration process, these grayscale values ​​are likely to have changed. For example, in the upper left corner grid area mentioned above, the grayscale value of the red channel is read in the second processed image to be 100, the grayscale value of the green channel is changed to 110, and the grayscale value of the blue channel is changed to 85. Record these updated grayscale values.

[0069] S404: Count the correspondence between the original grayscale values ​​and the updated grayscale values ​​of all color channels in all pixel regions to construct a mapping table.

[0070] A large number of recorded original grayscale values ​​and updated grayscale values ​​are arranged one by one to form a mapping table with a two-dimensional table structure. Taking the red channel as an example, one column of the table records the original red grayscale values ​​of each area in the first processed image, and the other column records the updated red grayscale values ​​of the same area in the second processed image. The green and blue channels construct their own sub-mapping tables in the same way. Finally, a complete mapping table covering the grayscale change relationship of all color channels and all pixel areas is integrated. The mapping table can be stored in the local storage chip of the display for quick query and call later.

[0071] By establishing such a detailed and precise mapping table, we can accurately capture the grayscale change pattern of the image after the two key steps of image content processing and image display effect calibration processing of the display, providing a reliable data basis for the subsequent restoration of the original information of the target image, just like building a precise bridge for the image's "time and space travel".

[0072] It should be noted that from the image signal input through the signal channel to the image seen on the display, it will automatically undergo image content processing and image display effect calibration processing, and these two layers of image processing bring challenges to the accurate acquisition of image information processed by the display. Because what we really want to acquire and analyze is the effect after the original image processing of the display, but the image display effect calibration processing will change the signal, making it difficult to directly obtain the true situation after the original image processing.

[0073] For example, after an image is processed by the display, the brightness increases to a certain extent, but the subsequent GAMMA correction changes the signal strength and distribution after the brightness increase. If we do not consider the impact of the correction processing and directly collect the image signal, we will get a result that is "interfered" by the correction processing, which cannot accurately reflect the real effect of the original image processing of the display. This is why it is necessary to establish a mapping table to remove the impact of the correction processing, so as to restore the real image information after the original image processing.

[0074] S50, collecting the target image after image content processing and image display effect calibration processing.

[0075] The target image is the image that needs to be captured. The target image sent to the display through the signal will automatically undergo image content processing and image display effect calibration.

[0076] S60 , performing grayscale redirection on the target image using the generated mapping table to obtain image information of the target image before image display effect calibration processing.

[0077] In one embodiment, step S60 specifically includes the following steps: S601 - S603 .

[0078] S601, obtaining grayscale feature information of all color channels in each pixel area in a target image.

[0079] According to the previous pixel area division method, the collected target image is divided into regions with the same structure again. For each region, the grayscale feature information of the three color channels of red (R), green (G), and blue (B) is extracted using an image analysis algorithm, including the grayscale value of the central pixel of the region and the distribution range of the grayscale value in the region. For example, in a certain area in the lower right corner of the target image, the grayscale value of the central pixel of the red channel is 130, and the grayscale value of the red channel in the region is distributed between 120-140; the grayscale value of the central pixel of the green channel is 140, and the grayscale value of the green channel in the region is distributed between 130-150; the grayscale value of the central pixel of the blue channel is 110, and the grayscale value of the blue channel in the region is distributed between 100-120.

[0080] S602: Look up the original grayscale value corresponding to the grayscale feature information extracted from the current pixel area in the mapping table.

[0081] The extracted grayscale feature information of each region and each color channel is used as an index to search and match in the previously constructed mapping table. For example, based on the grayscale feature information of the red channel in the lower right corner area, find the original grayscale value that best matches it in the red channel mapping table, assuming it is 100; similarly, find the corresponding original grayscale value in the green channel mapping table, assuming it is 110; find the corresponding original grayscale value in the blue channel mapping table, assuming it is 90.

[0082] S603: restore the current grayscale values ​​of all color channels of each pixel area to the original grayscale values.

[0083] Using the original grayscale value found, replace and update the grayscale value of the color channel of each pixel area in the target image. That is, replace the grayscale value of all pixels in the red channel of the lower right corner area with 100, replace the grayscale value of all pixels in the green channel with 110, replace the grayscale value of all pixels in the blue channel with 90, and so on, and complete the grayscale redirection operation for all areas and all color channels of the entire target image. Finally, reassemble these redirected areas and restore them to a complete image. The image obtained at this time is the image information of the target image before the image display effect calibration processing.

[0084] For steps S601-S603, through this series of operations, the influence of the image display effect calibration processing on the target image is successfully removed, and the original appearance of the target image after only image content processing is restored, allowing researchers to accurately analyze the image processing capabilities and effects of the display itself, providing a powerful technical means for improving display performance and optimizing image display quality, as if lifting the "veil" of the display processing effect and seeing the true face of the image.

[0085] The present invention establishes a mapping table of standard grayscale test images, and then performs grayscale redirection on the input target image according to the mapping table to obtain image information without image display effect calibration processing, thereby completing data collection and more realistically analyzing problems related to image processing.

[0086] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0087] The embodiment of the present invention further provides a display image acquisition device, which is used to perform the steps in any embodiment of the above display image acquisition method. Figure 2 , Figure 2 A schematic block diagram of a display image acquisition device 100 provided in an embodiment of the present application is shown. The display image acquisition device 100 specifically includes:

[0088] The acquisition unit 110 is used to acquire a standard grayscale test image; the first image processing unit 120 is used to perform image content processing on the standard grayscale test image to obtain a first processed image; the second image processing unit 130 is used to perform image display effect calibration processing on the first processed image to obtain a second processed image; the mapping table construction unit 140 is used to establish a mapping relationship between the first processed image and the second processed image, and generate a mapping table; the acquisition unit 150 is used to acquire a target image after image content processing and image display effect calibration processing; the grayscale redirection unit 160 is used to perform grayscale redirection on the target image using the generated mapping table to obtain image information of the target image before image display effect calibration processing.

[0089] In one embodiment, the mapping table construction unit 140 is specifically used to: divide the first processed image into a plurality of pixel areas; record the original grayscale values ​​of all color channels in each pixel area in the first processed image; record the updated grayscale values ​​of all color channels in the same pixel area as the first processed image in the second processed image; and count the correspondence between the original grayscale values ​​and the updated grayscale values ​​of all color channels in all pixel areas to construct a mapping table.

[0090] In one embodiment, the grayscale redirection unit 160 is specifically used to: obtain the grayscale feature information of all color channels in each pixel area in the target image; search the original grayscale value corresponding to the grayscale feature information extracted from the current pixel area in the mapping table; and restore the current grayscale value of all color channels of each pixel area to the original grayscale value.

[0091] It should be noted that those skilled in the art can clearly understand that the specific implementation process of the above-mentioned display image acquisition device 100 and each unit can refer to the corresponding description in the aforementioned method embodiment, and for the convenience and brevity of description, it will not be repeated here.

[0092] The above-mentioned display image acquisition device can be implemented in the form of a computer program. The computer program can be Figure 3 Runs on the computer device shown.

[0093] See also Figure 3 , Figure 3 700 is a schematic block diagram of a computer device provided in an embodiment of the present application. The computer device 700 may be a server, wherein the server may be an independent server or a server cluster composed of multiple servers.

[0094] like Figure 3 As shown, the computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the display image acquisition method as described above are implemented.

[0095] The computer device 700 includes a processor 720 , a memory, and a network interface 750 connected via a system bus 710 , wherein the memory may include a non-volatile storage medium 730 and an internal memory 740 .

[0096] The non-volatile storage medium 730 may store an operating system 731 and a computer program 732. When the computer program 732 is executed, the processor 720 may execute a display image acquisition method.

[0097] The processor 720 is used to provide computing and control capabilities and support the operation of the entire computer device 700.

[0098] The internal memory 740 provides an environment for the operation of the computer program 732 in the non-volatile storage medium 730. When the computer program 732 is executed by the processor 720, the processor 720 can execute the display image acquisition method.

[0099] The network interface 750 is used for network communication, such as sending assigned tasks, etc. Those skilled in the art will appreciate that Figure 3 The structure shown in the figure is only a block diagram of a part of the structure related to the present application scheme, and does not constitute a limitation on the computer device 700 to which the present application scheme is applied. The specific computer device 700 may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components. The processor 720 is used to run the program code stored in the memory to implement the display image acquisition method.

[0100] Those skilled in the art will understand that Figure 3 The embodiments of the computer device shown in the figure do not constitute a limitation on the specific composition of the computer device. In other embodiments, the computer device may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently. For example, in some embodiments, the computer device may only include a memory and a processor. In such embodiments, the structure and function of the memory and the processor are the same as those of the embodiment of the present invention. Figure 3 The embodiments shown are consistent and will not be described again here.

[0101] It should be understood that in the embodiment of the present application, the processor 720 may be a central processing unit (CPU), and the processor 720 may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0102] In another embodiment of the present invention, a computer-readable storage medium is provided. The computer-readable storage medium may be a non-volatile computer-readable storage medium. The computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, the display image acquisition method disclosed in the embodiment of the present invention is implemented.

[0103] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, the specific working process of the above-described equipment, devices and units can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here. Those of ordinary skill in the art can appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented with electronic hardware, computer software or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to the function. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0104] In the several embodiments provided by the present invention, it should be understood that the disclosed equipment, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. Units with the same function may also be combined into one unit. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interfaces, devices or units, or may be electrical, mechanical or other forms of connection.

[0105] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiments of the present invention.

[0106] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0107] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), disk or optical disk and other media that can store program codes.

[0108] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A display image acquisition method, characterized in that: include: Get a standard grayscale test image; Performing image content processing on the standard grayscale test image to obtain a first processed image; Performing image display effect calibration processing on the first processed image to obtain a second processed image; Establishing a mapping relationship between the first processed image and the second processed image, and generating a mapping table; Acquire the target image after image content processing and image display effect calibration; The generated mapping table is used to perform grayscale redirection on the target image to obtain image information of the target image before image display effect calibration processing.

2. A display image acquisition method according to claim 1, characterized in that: The standard grayscale test image is an image with 8-bit signal characteristics and covers a continuous transition from 0 to 255 grayscales.

3. A display image acquisition method according to claim 1, characterized in that: The image content processing includes at least one of the following: brightness adjustment, contrast adjustment and AI processing.

4. A display image acquisition method according to claim 1 or 3, characterized in that: The image display effect calibration process includes at least one of the following: GAMMA correction process, color temperature correction process and color gamut correction process.

5. A display image acquisition method according to claim 2, characterized in that: The step of establishing a mapping relationship between the first processed image and the second processed image and generating a mapping table includes: dividing the first processed image into a plurality of pixel regions; Recording the original grayscale values ​​of all color channels in each pixel area in the first processed image; Recording updated grayscale values ​​of all color channels in the same pixel region in the second processed image as in the first processed image; The correspondence between the original grayscale values ​​and the updated grayscale values ​​of all color channels in all pixel regions is counted to construct a mapping table.

6. A display image acquisition method according to claim 5, characterized in that: The pixel area is a collection of one or more gray levels.

7. A display image acquisition method according to claim 5, characterized in that: The grayscale redirection of the target image using the generated mapping table to obtain image information of the target image before the image display effect calibration process is performed includes: Obtain the grayscale feature information of all color channels in each pixel area in the target image; Find the original grayscale value corresponding to the grayscale feature information extracted from the current pixel area in the mapping table; Restore the current grayscale values ​​of all color channels of each pixel area to the original grayscale values.

8. A display image acquisition device, characterized in that: include: An acquisition unit, used for acquiring a standard grayscale test image; A first image processing unit, configured to perform image content processing on a standard grayscale test image to obtain a first processed image; A second image processing unit, used for performing image display effect calibration processing on the first processed image to obtain a second processed image; A mapping table building unit, used to establish a mapping relationship between the first processed image and the second processed image, and generate a mapping table; An acquisition unit, used for acquiring a target image after image content processing and image display effect calibration processing; The grayscale redirection unit is used to perform grayscale redirection on the target image using the generated mapping table to obtain image information of the target image before image display effect calibration processing.

9. A computer device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the display image acquisition method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and the computer program includes program instructions. When the program instructions are executed by a processor, the processor executes the display image acquisition method according to any one of claims 1 to 7.

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