A Mura compensation effect test method and system, electronic equipment and computer storage medium

Abstract

The application provides a Mura compensation effect test method and system, electronic equipment and computer storage medium, comprising: collecting first luminance data and second luminance data before and after Mura compensation under different gray scales of a frame; dividing a block unit according to the first luminance data and the second luminance data, and calculating error luminance values of each pixel in the frame; using the first luminance data, the second luminance data and the error luminance values, calculating luminance uniformity indexes and chroma uniformity indexes of the frame; and testing the Mura compensation effect according to the luminance uniformity indexes and the chroma uniformity indexes. The luminance data before and after Mura compensation is obtained, the luminance uniformity indexes and the chroma uniformity indexes are calculated according to the luminance data, the Mura compensation effect is tested, quantitative testing based on luminance uniformity and chroma uniformity is realized, the measurement standard of effect testing is unified, the reliability of test results is improved, and the problem of poor reliability of the existing Mura compensation effect test method is solved.

Description

Technical Field

[0001] This invention relates to the field of image processing technology, and in particular to a method and system for testing the Mura compensation effect, an electronic device, and a computer storage medium. Background Technology

[0002] AMOLED screens, with their superior physical properties, have become the preferred display solution for many electronic products. However, due to instabilities in the manufacturing process, screens often exhibit a mura phenomenon characterized by uneven brightness. Based on the shape of the mura, it can be categorized into linear mura, stripe mura, circular mura, and patchy mura, among others.

[0003] To eliminate mura, the Demura (Mura compensation) algorithm is currently commonly used to remove mura and improve display performance. However, the severity of mura defects varies across different screens; therefore, it is necessary to test the effectiveness of the Demura compensation algorithm to confirm whether the mura elimination meets expectations. However, current tests for mura compensation effectiveness rely on human visual observation, which not only lacks a unified measurement standard but is also highly susceptible to misjudgment due to visual fatigue, resulting in unreliable test results. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for testing the Mura compensation effect, an electronic device, and a computer storage medium to solve the problem of poor reliability in existing Mura compensation effect testing methods.

[0005] To address the aforementioned technical problems, this invention provides a method for testing the Mura compensation effect, comprising: Collect the first brightness data before Mura compensation and the second brightness data after Mura compensation at different gray levels of the image frame; The image is divided into blocks based on the first brightness data and the second brightness data, and the error brightness value of each pixel in the image is calculated. Using the first brightness data, the second brightness data, and the error brightness value, calculate the brightness uniformity index and color uniformity index of the image frame; The Mura compensation effect was confirmed based on the brightness uniformity index and the color uniformity index.

[0006] Optionally, in the Mura compensation effect testing method, the method of dividing the block into units based on the first luminance data and the second luminance data, and calculating the luminance error value, includes: The image frame is divided into several blocks of N×N pixels, where N is an integer greater than or equal to 3; The M×M pixels at the center of the block unit are taken as the center unit of the block unit, where M is an integer greater than or equal to 1; Using the first brightness data, calculate the average brightness of the central unit of each block; The second brightness data corresponding to each pixel in the block unit is subtracted from the average brightness of the block unit to obtain the error brightness value corresponding to each pixel in the block unit.

[0007] Optionally, in the Mura compensation effect testing method, the method for calculating the luminance uniformity index and chromaticity uniformity index using the first luminance data, the second luminance data, and the error luminance value includes: The sum of the error brightness values ​​of all pixels in each unit is calculated, and the average of the sum of the error brightness values ​​of all units is taken to obtain the brightness uniformity index. The first and second luminance data of all pixels are converted into chromaticity coordinates, and the chromaticity coordinates are quantized to obtain the chromaticity uniformity index.

[0008] Optionally, in the Mura compensation effect test method described above, the formula for calculating the brightness uniformity index is:

[0009] Where UOB represents the brightness uniformity index, X represents the number of block cells, and N×N represents the size of the block cells. This represents the error luminance value of the i-th pixel in the block id-th block unit. Indicates the target brightness of the image frame.

[0010] Optionally, in the Mura compensation effect test method, the target brightness is the average brightness of C×R pixels in the central area of ​​the image, where C and R are integers greater than or equal to 2.

[0011] Optionally, in the Mura compensation effect testing method, the method of converting the first luminance data and second luminance data of all pixels into chromaticity coordinates and quantizing the chromaticity coordinates to obtain the chromaticity uniformity index includes: Convert the first brightness data and the second brightness data into linear brightness data respectively; Using a color conversion matrix, linear luminance data is converted into tristimulus values ​​in the color space; The chromaticity coordinates of pixels are calculated using the tristimulus values ​​of the color space. The chromaticity uniformity index is calculated using the chromaticity coordinates corresponding to the first luminance data and the second luminance data.

[0012] Optionally, in the Mura compensation effect testing method, the formula used to convert the first luminance data and the second luminance data into linear luminance data is as follows:

[0013]

[0014]

[0015] in, , and These represent the first or second luminance data under the R, G, and B channels, respectively. , and These represent the linear luminance data obtained from the downconversion of the R, G, and B channels, respectively, with Gamma representing the gamma voltage value used for correction.

[0016] Optionally, in the Mura compensation effect testing method, the formula for calculating the chromaticity coordinates of a pixel using the tristimulus values ​​of the color space is:

[0017]

[0018] Where x represents the horizontal coordinate of the pixel's chromaticity coordinates, y represents the vertical coordinate of the pixel's chromaticity coordinates, and X, Y, and Z are the tristimulus values ​​of the color space.

[0019] Optionally, in the Mura compensation effect test method, the formula for calculating the chromaticity uniformity index is:

[0020] Where UOC represents the color uniformity index, X represents the number of block units, N×N represents the size of the block units, and blockid represents the block unit number. This represents the x-coordinate of the chromaticity coordinates corresponding to the first luminance data of the i-th pixel. This represents the ordinate of the chromaticity coordinates corresponding to the first luminance data of the i-th pixel. This represents the x-coordinate of the chromaticity coordinates corresponding to the second luminance data of the i-th pixel. The ordinate represents the chromaticity coordinate corresponding to the second luminance data of the i-th pixel.

[0021] Optionally, in the Mura compensation effect test method, the formula used to confirm the Mura compensation effect based on the luminance uniformity index and the chromaticity uniformity index is:

[0022] in, The scores represent the test results. UOB represents the luminance uniformity index, and UOC represents the chromaticity uniformity index. Represents an empirical constant, 0 ≤ ≤1.

[0023] To address the aforementioned technical problems, the present invention also provides a Mura compensation effect testing system for implementing the Mura compensation effect testing method as described in any of the preceding claims, wherein the Mura compensation effect testing system comprises: The acquisition module is used to acquire the first brightness data before Mura compensation and the second brightness data after Mura compensation at different gray levels of the image frame; The segmentation module is used to divide the image into block units based on the first brightness data and the second brightness data, and to calculate the error brightness value of each pixel in the image frame. The calculation module is used to calculate the brightness uniformity index and color uniformity index of the image frame using the first brightness data, the second brightness data, and the error brightness value. The testing module is used to confirm the Mura compensation effect based on the brightness uniformity index and the color uniformity index.

[0024] To address the aforementioned technical problems, the present invention also provides an electronic device, including a memory, a processor, and an executable program stored in the memory and capable of being run by the processor; when the processor runs the executable program, it performs the Mura compensation effect testing method as described in any of the preceding claims.

[0025] To address the aforementioned technical problems, the present invention also provides a computer storage medium storing an executable program; when the executable program is executed, it implements the Mura compensation effect testing method as described in any of the preceding claims.

[0026] The present invention provides a method, system, electronic device, and computer storage medium for testing the Mura compensation effect, comprising: acquiring first brightness data before Mura compensation and second brightness data after Mura compensation at different gray levels of the image frame; dividing the image frame into block units based on the first and second brightness data, and calculating the error brightness value of each pixel in the image frame; calculating the brightness uniformity index and chromaticity uniformity index of the image frame using the first brightness data, the second brightness data, and the error brightness value; and confirming the Mura compensation effect based on the brightness uniformity index and chromaticity uniformity index. By acquiring brightness data before and after Mura compensation, and calculating the brightness uniformity index and chromaticity uniformity index based on the brightness data, the Mura compensation effect is tested, realizing quantitative testing based on brightness uniformity and chromaticity uniformity, unifying the measurement standard for effect testing, improving the reliability of test results, and solving the problem of poor reliability in existing Mura compensation effect testing methods. Attached Figure Description

[0027] Figure 1This is a flowchart of the Mura compensation effect testing method provided in this embodiment; Figure 2 This is a structural example diagram of a 4×4 block unit provided in this embodiment; Figure 3 This is an example diagram of the error brightness value within a block cell provided in this embodiment; Figure 4 This is a structural block diagram of the Mura compensation effect testing system provided in this embodiment. Detailed Implementation

[0028] The following detailed description, in conjunction with the accompanying drawings and specific embodiments, provides a further detailed explanation of the Mura compensation effect testing method and system, electronic device, and computer storage medium proposed in this invention. It should be noted that the drawings are all in a very simplified form and use non-precise scales, intended only to facilitate and clarify the illustration of the embodiments of the invention. Furthermore, the structures shown in the drawings are often part of the actual structures. In particular, different figures may emphasize different aspects and sometimes use different scales.

[0029] It should be noted that the terms "first," "second," etc., used in the specification, claims, and drawings of this invention are used to distinguish similar objects in order to describe embodiments of the invention, and are not used to describe a specific order or sequence. It should be understood that such uses of terminology are interchangeable where appropriate. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0030] To clearly explain the implementation scheme of the Mura compensation effect testing method and system, electronic device and computer storage medium provided in this embodiment, the technical terms involved in this embodiment are explained as follows: AMOLED: Active-matrix organic light-emitting diode, is a display technology. OLED: Organic Light-Emitting Diode, is a current-driven organic light-emitting device that emits light through carrier injection and recombination. Its luminous intensity is proportional to the injection current. Mura: Regional brightness or color unevenness (cloud-like, mottled defects) in displays (especially OLED / AMOLED) under uniform screen conditions, which are caused by manufacturing or driving non-uniformity such as TFT threshold variation, OLED material aging, and backlight unevenness. Demura: Mura compensation is an external optical compensation process. The main steps include illuminating the panel, high-precision CCD multi-grayscale image acquisition, algorithm recognition of Mura distribution, calculation of compensation value, generation and burning of LUT to Flash / OTP, and real-time correction output during driving. CIE color space: It is one of the RGB color spaces and is known for its specific set of monochrome (single wavelength) primary colors.

[0031] This embodiment provides a method for testing the Mura compensation effect, such as... Figure 1 As shown, it includes: S1, collect the first brightness data before Mura compensation and the second brightness data after Mura compensation at different gray levels of the image frame; S2, divide the image into block units based on the first brightness data and the second brightness data, and calculate the error brightness value of each pixel in the image frame; S3, using the first brightness data, the second brightness data, and the error brightness value, calculate the brightness uniformity index and color uniformity index of the image frame; S4. Confirm the Mura compensation effect based on the brightness uniformity index and the color uniformity index.

[0032] The Mura compensation effect testing method provided in this embodiment obtains luminance data before and after Mura compensation, and calculates luminance uniformity index and chromaticity uniformity index based on the luminance data to test the Mura compensation effect. It realizes quantitative testing based on luminance uniformity and chromaticity uniformity, unifies the measurement standard of effect testing, improves the reliability of test results, and solves the problem of poor reliability of existing Mura compensation effect testing methods.

[0033] Specifically, in this embodiment, step S1 involves collecting the first brightness data before Mura compensation and the second brightness data after Mura compensation at different gray levels of the image frame.

[0034] In practical applications, the Demura system can be used to collect brightness data corresponding to different gray levels (such as 16, 32, 96, 160, 192 and 224 gray levels) of the three RGB channels under the display panel, thereby obtaining multiple sets of first and second brightness data for a single channel.

[0035] Furthermore, in this embodiment, step S2, the method for dividing the image into block units based on the first brightness data and the second brightness data, and calculating the error brightness value of each pixel in the image frame, includes: S21, divide the image frame into several block units of size N×N pixels, where N is an integer greater than or equal to 3.

[0036] In one specific embodiment, for example, the image frame is divided into several block units of 4×4 pixels each, and the block units are adjacent and do not overlap.

[0037] S22, take the M×M pixels at the center position of the block unit as the center unit of the block unit, where M is an integer greater than or equal to 1.

[0038] Taking a 4x4 block unit as an example, such as Figure 2 As shown, the 2×2 pixels (L21, L22, L31 and L32) at the center position can be used as the center unit of this block.

[0039] Of course, in other embodiments, the size of the block unit and the size of the center unit can be reasonably set according to the pixel size of the image frame, and this application does not limit this.

[0040] S23, using the first brightness data, calculate the average brightness of the center unit of each block.

[0041] Specifically, in this embodiment, the average value of the first brightness data corresponding to the pixels of the central unit in each unit is calculated to obtain the average brightness.

[0042] Taking the above example, the average brightness L mid =(L21+L22+L31+L32) / 4, where L21, L22, L31 and L32 are the first brightness data corresponding to the pixels of the central unit.

[0043] S24, the second brightness data corresponding to each pixel in the block unit is subtracted from the average brightness of the block unit to obtain the error brightness value corresponding to each pixel in the block unit.

[0044] Among them, such as Figure 3 As shown, the error brightness value corresponding to the pixel of the center unit in the block unit is the center error brightness (N1, N2, N3 and N4), and the error brightness value corresponding to the pixel of the other position in the block unit is the boundary error brightness (Q10, Q11, Q12, Q13, Q20, Q23, Q30, Q33, Q40, Q41, Q42 and Q43).

[0045] This embodiment divides the image frame into blocks and defines a central unit within each block. The error brightness value for each pixel is obtained based on the average brightness of the central unit, enabling accurate evaluation of brightness uniformity with simple calculations.

[0046] Furthermore, in this embodiment, step S3, the method for calculating the brightness uniformity index and color uniformity index of the image frame using the first brightness data, the second brightness data, and the error brightness value, includes: S31, calculate the sum of the error brightness values ​​of all pixels in each block, and take the average of the sum of the error brightness values ​​of all blocks to obtain the brightness uniformity index.

[0047] Specifically, in this embodiment, after averaging the sum of the error brightness values ​​of all block units, it is necessary to divide by the target brightness at the corresponding gray level of the error brightness value to perform normalization processing and obtain the final brightness uniformity index.

[0048] This embodiment provides the calculation formula for the brightness uniformity index, as follows:

[0049] Where UOB represents the brightness uniformity index, X represents the number of block cells, and N×N represents the size of the block cells. This represents the error luminance value of the i-th pixel in the block id-th block unit. Indicates the target brightness of the image frame.

[0050] In practical applications, the target brightness is the average brightness of C×R pixels in the central region of the image, where C and R are integers greater than or equal to 2. For example, the average brightness of 20×20 pixels in the central region of the image can be selected as the target brightness for the entire image. Of course, the size of the area selected for calculating the target brightness can be reasonably and flexibly set according to the actual situation such as the image size, and this application does not impose any restrictions on this.

[0051] The brightness uniformity index UOB provided in this embodiment measures the ratio of the brightness error of each block unit in the image to the brightness of the central target. The average ratio. The smaller the brightness uniformity index UOB, the better the brightness uniformity; the larger the brightness uniformity index UOB, the worse the brightness uniformity.

[0052] This embodiment calculates the brightness uniformity index by using the error brightness value, thereby achieving a quantitative assessment of the brightness uniformity of the image before and after Mura compensation and improving the reliability of testing the brightness uniformity in the Mura compensation effect.

[0053] S32 converts the first and second luminance data of all pixels into chromaticity coordinates, quantizes the chromaticity coordinates, and obtains the chromaticity uniformity index.

[0054] Specifically, in this embodiment, firstly, the first luminance data and the second luminance data are converted into linear luminance data, respectively. Considering that the luminance data currently collected by the Demura system is... , and Furthermore, since this brightness value was acquired after gamma voltage correction, the following formula can be used for conversion when converting it to linear brightness data:

[0055]

[0056]

[0057] in, , and These represent the first or second luminance data under the R, G, and B channels, respectively. , and These represent the linear luminance data obtained by converting the first or second luminance data under the R, G, and B channels, respectively, with Gamma representing the gamma voltage value used for correction.

[0058] Then, using a color conversion matrix, the linear luminance data is converted into tristimulus values ​​in a color space. Specifically, it can be converted into CIE color space tristimulus values. In one specific embodiment, assuming an sRGB color space (D65 white point) color conversion matrix is ​​used, the CIE color space tristimulus values ​​are calculated as follows:

[0059] Where X, Y, and Z represent the tristimulus values ​​of the color space.

[0060] Next, the chromaticity coordinates of the pixels are calculated using the tristimulus values ​​of the color space. Specifically, in this embodiment, the formula for calculating the chromaticity coordinates is as follows:

[0061]

[0062] Where x represents the horizontal coordinate of the pixel's chromaticity coordinates, y represents the vertical coordinate of the pixel's chromaticity coordinates, and X, Y, and Z are the tristimulus values ​​of the color space.

[0063] Finally, the chromaticity uniformity index is calculated using the chromaticity coordinates corresponding to the first luminance data and the second luminance data. Specifically, in this embodiment, the calculation formula for the chromaticity uniformity index is given as follows:

[0064] Where UOC represents the color uniformity index, X represents the number of block units, N×N represents the size of the block units, and blockid represents the block unit number. This represents the x-coordinate of the chromaticity coordinates corresponding to the first luminance data of the i-th pixel. This represents the ordinate of the chromaticity coordinates corresponding to the first luminance data of the i-th pixel. This represents the x-coordinate of the chromaticity coordinates corresponding to the second luminance data of the i-th pixel. The ordinate represents the chromaticity coordinate corresponding to the second luminance data of the i-th pixel.

[0065] The color uniformity index UOC provided in this embodiment measures the color coordinate error of each pixel in the image. The smaller the color uniformity index UOC, the better the color uniformity; the larger the color uniformity index UOC, the worse the color uniformity.

[0066] This embodiment calculates the color uniformity index using first and second brightness data, enabling a quantitative assessment of the color uniformity of the image frame before and after Mura compensation, thus improving the reliability of the test for color uniformity in the Mura compensation effect.

[0067] Furthermore, in this embodiment, step S4 confirms the Mura compensation effect based on the brightness uniformity index and the color uniformity index.

[0068] Specifically, in this embodiment, the formula used to test the Mura compensation effect is:

[0069] in, The scores represent the test results. UOB represents the luminance uniformity index, and UOC represents the chromaticity uniformity index. Represents an empirical constant, 0 ≤ ≤1.

[0070] In practical applications, empirical constants can be adjusted reasonably according to actual needs. The values ​​of can be adjusted to determine the relative importance of the luminance uniformity index UOB and the chromaticity uniformity index UOC in the testing system. Additionally, a score threshold can be set; if the calculated test result score exceeds the threshold, the Mura compensation effect is considered to meet expectations; otherwise, the Mura compensation effect is considered to fail to meet expectations.

[0071] The Mura compensation effect testing method provided in this embodiment tests the Mura compensation effect by calculating the error luminance value based on block units and further calculating the luminance uniformity index and chromaticity uniformity index. This achieves a quantitative comprehensive test based on luminance uniformity and chromaticity uniformity, unifies the measurement standard for effect testing, improves the reliability of test results, and solves the problem of poor reliability in existing Mura compensation effect testing methods.

[0072] This embodiment also provides a Mura compensation effect testing system for implementing the Mura compensation effect testing method described above, such as... Figure 4 As shown, the Mura compensation effect testing system includes: The acquisition module is used to acquire the first brightness data before Mura compensation and the second brightness data after Mura compensation at different gray levels of the image frame; The segmentation module is used to divide the image into block units based on the first brightness data and the second brightness data, and to calculate the error brightness value of each pixel in the image frame. The calculation module is used to calculate the brightness uniformity index and color uniformity index of the image frame using the first brightness data, the second brightness data, and the error brightness value. The testing module is used to confirm the Mura compensation effect based on the brightness uniformity index and the color uniformity index.

[0073] Furthermore, this embodiment also provides an electronic device, including a memory, a processor, and an executable program stored in the memory and capable of being run by the processor; when the processor runs the executable program, it performs the Mura compensation effect test method as described above.

[0074] Furthermore, this embodiment also provides a computer storage medium storing an executable program; when the executable program is executed, it implements the Mura compensation effect testing method as described above.

[0075] It should be noted that the various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Similar or identical parts between embodiments can be referred to mutually. In addition, different parts between embodiments can also be combined with each other, and this invention does not limit this.

[0076] The Mura compensation effect testing method, system, electronic device, and computer storage medium provided in this embodiment include: acquiring first brightness data before Mura compensation and second brightness data after Mura compensation at different gray levels of the image frame; dividing the image frame into block units based on the first and second brightness data, and calculating the error brightness value of each pixel; calculating the brightness uniformity index and chromaticity uniformity index of the image frame using the first brightness data, the second brightness data, and the error brightness value; and confirming the Mura compensation effect based on the brightness uniformity index and chromaticity uniformity index. By acquiring brightness data before and after Mura compensation, and calculating the brightness uniformity index and chromaticity uniformity index based on the brightness data, the Mura compensation effect is tested, realizing quantitative testing based on brightness uniformity and chromaticity uniformity, unifying the measurement standard for effect testing, improving the reliability of test results, and solving the problem of poor reliability in existing Mura compensation effect testing methods.

[0077] The above description is merely a description of preferred embodiments of the present invention and is not intended to limit the scope of the present invention in any way. Any changes or modifications made by those skilled in the art based on the above disclosure shall fall within the protection scope of the claims.

Claims

1. A method for testing the Mura compensation effect, characterized in that, include: Collect the first brightness data before Mura compensation and the second brightness data after Mura compensation at different gray levels of the image frame; The image is divided into blocks based on the first brightness data and the second brightness data, and the error brightness value of each pixel in the image is calculated. Using the first brightness data, the second brightness data, and the error brightness value, calculate the brightness uniformity index and color uniformity index of the image frame; The Mura compensation effect was confirmed based on the brightness uniformity index and the color uniformity index.

2. The Mura compensation effect testing method according to claim 1, characterized in that, The method for dividing the data into block units based on the first brightness data and the second brightness data, and calculating the brightness error value, includes: The image frame is divided into several blocks of N×N pixels, where N is an integer greater than or equal to 3; The M×M pixels at the center of the block unit are taken as the center unit of the block unit, where M is an integer greater than or equal to 1; Using the first brightness data, calculate the average brightness of the central unit of each block; The second brightness data corresponding to each pixel in the block unit is subtracted from the average brightness of the block unit to obtain the error brightness value corresponding to each pixel in the block unit.

3. The Mura compensation effect testing method according to claim 1, characterized in that, The method for calculating the luminance uniformity index and the chromaticity uniformity index using the first luminance data, the second luminance data, and the error luminance value includes: The sum of the error brightness values ​​of all pixels in each unit is calculated, and the average of the sum of the error brightness values ​​of all units is taken to obtain the brightness uniformity index. The first and second luminance data of all pixels are converted into chromaticity coordinates, and the chromaticity coordinates are quantized to obtain the chromaticity uniformity index.

4. The Mura compensation effect testing method according to claim 3, characterized in that, The formula for calculating the brightness uniformity index is as follows: Where UOB represents the brightness uniformity index, X represents the number of block cells, and N×N represents the size of the block cells. This represents the error luminance value of the i-th pixel in the block id-th block unit. Indicates the target brightness of the image frame.

5. The Mura compensation effect testing method according to claim 4, characterized in that, The target brightness is the average brightness of C×R pixels in the central area of ​​the image, where C and R are integers greater than or equal to 2.

6. The Mura compensation effect testing method according to claim 3, characterized in that, The method for converting the first and second luminance data of all pixels into chromaticity coordinates, and quantizing the chromaticity coordinates to obtain a chromaticity uniformity index includes: Convert the first brightness data and the second brightness data into linear brightness data respectively; Using a color conversion matrix, linear luminance data is converted into tristimulus values ​​in the color space; The chromaticity coordinates of pixels are calculated using the tristimulus values ​​of the color space. The chromaticity uniformity index is calculated using the chromaticity coordinates corresponding to the first luminance data and the second luminance data.

7. The Mura compensation effect testing method according to claim 6, characterized in that, The formulas used to convert the first brightness data and the second brightness data into linear brightness data are as follows: in, , and These represent the first or second luminance data under the R, G, and B channels, respectively. , and These represent the linear luminance data obtained from the downconversion of the R, G, and B channels, respectively, with Gamma representing the gamma voltage value used for correction.

8. The Mura compensation effect testing method according to claim 6, characterized in that, The formula for calculating the chromaticity coordinates of a pixel using the tristimulus values ​​of the color space is as follows: Where x represents the horizontal coordinate of the pixel's chromaticity coordinates, y represents the vertical coordinate of the pixel's chromaticity coordinates, and X, Y, and Z are the tristimulus values ​​of the color space.

9. The method for testing the Mura compensation effect according to claim 6, characterized in that, The formula for calculating the color uniformity index is as follows: Where UOC represents the color uniformity index, X represents the number of block units, N×N represents the size of the block units, and blockid represents the block unit number. This represents the x-coordinate of the chromaticity coordinates corresponding to the first luminance data of the i-th pixel. This represents the ordinate of the chromaticity coordinates corresponding to the first luminance data of the i-th pixel. This represents the x-coordinate of the chromaticity coordinates corresponding to the second luminance data of the i-th pixel. The ordinate represents the chromaticity coordinate corresponding to the second luminance data of the i-th pixel.

10. The method for testing the Mura compensation effect according to claim 1, characterized in that, The formula used to determine the Mura compensation effect based on the luminance uniformity index and the chromaticity uniformity index is as follows: in, The scores represent the test results. UOB represents the luminance uniformity index, and UOC represents the chromaticity uniformity index. Represents an empirical constant, 0 ≤ ≤1.

11. A Mura compensation effect testing system, used to implement the Mura compensation effect testing method as described in any one of claims 1 to 10, characterized in that, The Mura compensation effect testing system includes: The acquisition module is used to acquire the first brightness data before Mura compensation and the second brightness data after Mura compensation at different gray levels of the image frame; The segmentation module is used to divide the image into block units based on the first brightness data and the second brightness data, and to calculate the error brightness value of each pixel in the image frame. The calculation module is used to calculate the brightness uniformity index and color uniformity index of the image frame using the first brightness data, the second brightness data, and the error brightness value. The testing module is used to confirm the Mura compensation effect based on the brightness uniformity index and the color uniformity index.

12. An electronic device, characterized in that, It includes a memory, a processor, and an executable program stored in the memory and capable of being run by the processor; when the processor runs the executable program, it performs the Mura compensation effect testing method as described in any one of claims 1 to 10.

13. A computer storage medium, characterized in that, The computer storage medium stores an executable program; when the executable program is executed, it implements the Mura compensation effect testing method as described in any one of claims 1 to 10.

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