A brightness compensation method, device and storage medium based on step-by-step processing

Abstract

The present application discloses a brightness compensation method, device, and storage medium based on step-by-step processing, which are used to improve the brightness compensation efficiency of a new display screen. The method comprises the following steps: obtaining a captured image; obtaining the position data and brightness data of each pixel; modeling the brightness compensation coefficients of all captured images to generate relationship matrix data; adjusting the relationship matrix data according to the brightness data, position data, and predetermined data order of each pixel in each captured image to generate a brightness compensation coefficient expression; decomposing and optimizing the brightness transformation matrix corresponding to the brightness order matrix data in the brightness compensation coefficient expression to generate a result matrix; sequentially generating coefficient images of each pixel from the result matrix; integrating the coefficient image and the captured image for pixels at the same position in units of images according to the pixel position matrix to generate a brightness compensation coefficient; and using the brightness compensation coefficient to compensate the brightness of each pixel.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of display screen detection, and in particular to a brightness compensation method based on step-by-step processing. Background Art

[0002] With the continuous development of the display industry, displays are becoming increasingly versatile and complex, with increasingly sophisticated designs. Examples include large-size displays, flexible displays, spliced ​​curved displays, ultra-high-resolution displays, and ultra-narrow bezel displays. With the increasing popularity of these new display technologies, display unevenness (mura) has become a major concern. Mura is often caused by factors such as the production process and raw material purity of different display types.

[0003] In the field of new display panels, the main technologies currently used to compensate for display mura include global brightness adjustment and regional brightness correction. The brightness compensation algorithm (or demura) adjusts the brightness of each pixel on a display. The relationship between brightness and each pixel is derived from multiple captured grayscale images, primarily through mathematical modeling. As new display screens continue to increase in sophistication and the resolution of captured images used for brightness compensation continues to rise, the amount of data required to solve the pixel-by-pixel coefficient vectors for brightness compensation is exponentially increasing. This results in extremely large computational workloads, significantly increased computation time, and poor numerical stability, leading to reduced brightness compensation efficiency for new display screens. Summary of the Invention

[0004] The present application discloses a brightness compensation method, device and storage medium based on step-by-step processing, which are used to improve the brightness compensation efficiency of a new display screen.

[0005] In a first aspect, an embodiment of the present application provides a brightness compensation method based on step-by-step processing, comprising:

[0006] Obtain N captured images of the display screen to be tested at different preset display grayscales, where N is an integer greater than or equal to 2; obtain position data and brightness data of each pixel in each captured image; model the brightness compensation coefficients of all captured images to generate relationship matrix data, which includes brightness compensation coefficient matrix data, pixel position matrix data, and brightness order matrix data; adjust the relationship matrix data according to the brightness data, position data, and predetermined data order of each pixel in each captured image to generate a brightness compensation coefficient expression; decompose and optimize the brightness transformation matrix corresponding to the brightness order matrix data in the brightness compensation coefficient expression to generate a result matrix; sequentially generate N*N coefficient images from the elements of the result matrix, and the value of each coefficient image is any element of the result matrix; step-by-step process the NxN coefficient images and the N captured images, and integrate the coefficient images and the captured images for pixels at the same position in units of images according to the pixel position matrix to generate a brightness compensation coefficient; and use the brightness compensation coefficient to compensate for the brightness of each pixel.

[0007] Optionally, the step of decomposing and optimizing the brightness transformation matrix corresponding to the brightness order matrix data in the brightness compensation coefficient expression to generate the result matrix includes:

[0008] The QR decomposition method is used to decompose and optimize the brightness transformation matrix corresponding to the brightness order matrix data in the brightness compensation coefficient expression to generate a result matrix.

[0009] Optionally, the steps of using a QR decomposition method to decompose and optimize the brightness transformation matrix corresponding to the brightness order matrix data in the brightness compensation coefficient expression, and generating the result matrix include:

[0010] Perform QR decomposition optimization on the brightness transformation matrix corresponding to the brightness order matrix data in the brightness compensation coefficient expression to generate an orthogonal data set and a triangular data set;

[0011] Generates a result matrix based on the orthogonal decomposition data and the triangular decomposition data.

[0012] Optionally, NxN coefficient images and N acquired images are processed in steps, and the coefficient images and acquired images are integrated step by step for pixels at the same position in units of images according to the pixel position matrix. The step of generating the brightness compensation coefficient includes: determining the coefficient image of the first row in the NxN coefficient images and the corresponding first acquired image, integrating the pixels at the same position in units of images according to the pixel position matrix, and generating a first step-by-step processing result; determining the coefficient image of the second row in the NxN coefficient images and the corresponding second acquired image, integrating the pixels at the same position in units of images according to the pixel position matrix, and then combining the integration result with the first step-by-step processing result to generate a second step-by-step processing result; and so on, determining the coefficient image of the Nth row and the corresponding Nth acquired image, integrating the pixels at the same position in units of images according to the pixel position matrix, and then combining the integration result with the N-1th step-by-step processing result to generate a target processing result; and determining the target processing result as the brightness compensation coefficient.

[0013] Optionally, after the steps of acquiring N captured images of the display screen to be tested at different preset display grayscales, and acquiring position data and brightness data of each pixel in each captured image, the brightness compensation method further includes:

[0014] Perform image preprocessing on N captured images to eliminate lens distortion, noise, and redundant background areas.

[0015] Optionally, the step of obtaining N captured images of the display screen to be tested at different preset display grayscales includes:

[0016] Light up the display screen to be tested with different preset grayscale images, and light up the center point area of ​​the display screen to be tested;

[0017] Adjust the position of the sampling camera so that the sampling center of the sampling camera is aligned with the center point of the display screen to be tested;

[0018] The sampling camera is used to collect images at the center point of the center point area to generate a collected image.

[0019] Optionally, the display screen to be tested is a display screen composed of several flexible spliced ​​screens; the step of obtaining N captured images of the display screen to be tested at different preset display grayscales includes: combining the flexible spliced ​​screens to form a display screen to be tested; lighting the display screen to be tested at different preset display grayscales, lighting the central point area of ​​the display screen to be tested, and lighting the central pixel point of each flexible spliced ​​screen; adjusting the position of the sampling camera so that the sampling center of the sampling camera is aligned with the central point of the central point area, and capturing a first image to be adjusted at the central point of the central point area through the sampling camera; performing a warpage analysis on the display screen to be tested based on the position coordinates of the central point area in the first image to be adjusted, the coordinate information and grayscale information of the central pixel point of each flexible spliced ​​screen; when the warpage analysis result shows that there is no flexible splicing warpage defect, lighting the display screen to be tested at different preset display grayscales, capturing through the sampling camera, and generating a captured image;

[0020] When the warping analysis result shows that there is a flexible splicing warping defect, the flexible splicing screen with the flexible splicing warping defect is replaced according to the warping analysis result;

[0021] The replaced display screen to be tested is imaged again until the flexible splicing warping defect no longer exists, and the image is recaptured by the sampling camera to generate an image.

[0022] Optionally, the step of performing a warping analysis on the display screen to be tested according to the position coordinates of the center point area in the first image to be adjusted, the coordinate information of the center pixel point of each flexible spliced ​​display screen, and the grayscale information includes: expanding the splicing screen points according to the position coordinates of the center point area in the first image to be adjusted, and generating a reference midpoint on each flexible spliced ​​screen area; performing a collective orientation deviation analysis on the coordinate information of the center pixel point of each flexible spliced ​​display screen on the first image to be adjusted and the reference midpoint; when the analysis result shows that there is a warping defect, determining the first image to be adjusted according to the collective orientation deviation analysis result. Adjust the warping defect area on the image, where the warping defect area consists of at least one flexible splicing display area; generate several grayscale gradient images based on the warping defect direction information of the collective directional deviation analysis results and a preset gradient degree, where the gradient degree is determined by the size of the flexible splicing screen; light up the grayscale gradient images on the flexible splicing screen corresponding to the warping defect area; adjust the position of the sampling camera so that the sampling center of the sampling camera is aligned with the center point of the flexible splicing screen, and collect the warping defect detection image through the sampling camera; perform warping grayscale gradient analysis on the warping defect detection image to generate a warping analysis result.

[0023] In a second aspect, an embodiment of the present application provides a brightness compensation device based on step-by-step processing, comprising: a first acquisition unit for acquiring N captured images of a display screen to be tested at different preset display grayscales, where N is an integer greater than or equal to 2; a second acquisition unit for acquiring position data and brightness data of each pixel in each captured image; a first generation unit for modeling the brightness compensation coefficients of all captured images and generating relationship matrix data, the relationship matrix data including brightness compensation coefficient matrix data, pixel position matrix data and brightness order matrix data; a second generation unit for generating a relationship matrix based on the brightness data, position data and predetermined data order of each pixel in each captured image. The matrix data is adjusted to generate a brightness compensation coefficient expression; the third generation unit is used to decompose and optimize the brightness transformation matrix corresponding to the brightness order matrix data in the brightness compensation coefficient expression to generate a result matrix; the fourth generation unit is used to sequentially generate N*N coefficient images from the elements of the result matrix, and the value of each coefficient image is any element of the result matrix; the fifth generation unit is used to process the NxN coefficient images and the N acquired images in steps, and integrate the coefficient images and the acquired images for pixels at the same position in units of images according to the pixel position matrix to generate a brightness compensation coefficient; the compensation unit is used to compensate the brightness of each pixel point using the brightness compensation coefficient.

[0024] Optionally, the third generation unit includes:

[0025] The QR decomposition method is used to decompose and optimize the brightness transformation matrix corresponding to the brightness order matrix data in the brightness compensation coefficient expression to generate a result matrix.

[0026] Optionally, the third generation unit includes:

[0027] Perform QR decomposition optimization on the brightness transformation matrix corresponding to the brightness order matrix data in the brightness compensation coefficient expression to generate an orthogonal data set and a triangular data set;

[0028] Generates a result matrix based on the orthogonal decomposition data and the triangular decomposition data.

[0029] Optionally, the fifth generation unit includes: determining the coefficient image of the first row in the NxN coefficient images and the corresponding first acquisition image, integrating the pixels at the same position according to the pixel position matrix and in units of images, and generating a first step-by-step processing result; determining the coefficient image of the second row in the NxN coefficient images and the corresponding second acquisition image, integrating the pixels at the same position according to the pixel position matrix and in units of images, and then combining the integration result with the first step-by-step processing result to generate a second step-by-step processing result; and so on, determining the coefficient image of the Nth row and the corresponding Nth acquisition image, integrating the pixels at the same position according to the pixel position matrix and in units of images, and then combining the integration result with the N-1th step-by-step processing result to generate a target processing result; and determining the target processing result as the brightness compensation coefficient.

[0030] Optionally, after the steps of acquiring N captured images of the display screen to be tested at different preset display grayscales, and acquiring position data and brightness data of each pixel in each captured image, the brightness compensation method further includes:

[0031] Perform image preprocessing on N captured images to eliminate lens distortion, noise, and redundant background areas.

[0032] Optionally, the step of obtaining N captured images of the display screen to be tested at different preset display grayscales includes:

[0033] Light up the display screen to be tested with different preset grayscale images, and light up the center point area of ​​the display screen to be tested;

[0034] Adjust the position of the sampling camera so that the sampling center of the sampling camera is aligned with the center point of the display screen to be tested;

[0035] The sampling camera is used to collect images at the center point of the center point area to generate a collected image.

[0036] Optionally, the display screen to be tested is a display screen composed of several flexible spliced ​​screens; the first acquisition unit includes: a splicing module for combining the flexible spliced ​​screens to form a display screen to be tested; a first lighting module for lighting the display screen to be tested with different preset display grayscale images, lighting the central point area of ​​the display screen to be tested, and lighting the central pixel point of each flexible spliced ​​screen; a first acquisition module for adjusting the position of the sampling camera so that the sampling center of the sampling camera is aligned with the central point of the central point area, and collecting the first image to be adjusted at the central point of the central point area by the sampling camera; an analysis module for analyzing the position of the central point area in the first image to be adjusted The coordinates, coordinate information and grayscale information of the central pixel point of each flexible splicing display screen are used to perform warpage analysis on the display screen to be tested; the second acquisition module is used to light up the display screen to be tested with different preset display grayscale images when the warpage analysis result shows that there is no flexible splicing warpage defect, and collect the images through the sampling camera to generate a collected image; the replacement module is used to replace the flexible splicing screen with the flexible splicing warpage defect according to the warpage analysis result when the warpage analysis result shows that there is a flexible splicing warpage defect; the generation module is used to collect images of the replaced display screen to be tested again until there is no flexible splicing warpage defect, and re-collect the images through the sampling camera to generate a collected image.

[0037] Optionally, the analysis module includes: expanding the splicing screen points according to the position coordinates of the center point area in the first image to be adjusted, and generating a reference midpoint on each flexible splicing screen area; performing collective directional deviation analysis on the coordinate information of the center pixel point of each flexible splicing display screen on the first image to be adjusted and the reference midpoint; when the analysis result shows that there is a warping defect, determining the warping defect area on the first image to be adjusted according to the collective directional deviation analysis result, and the warping defect area is composed of at least one flexible splicing display screen area; generating a number of grayscale gradient images according to the warping defect direction information of the collective directional deviation analysis result and a preset gradient degree, and the gradient degree is determined by the size of the flexible splicing screen; lighting the grayscale gradient image on the flexible splicing screen corresponding to the warping defect area; adjusting the sampling camera position so that the sampling center of the sampling camera is aligned with the center point of the flexible splicing screen, and collecting the warping defect detection image through the sampling camera; performing warping grayscale gradient analysis on the warping defect detection image to generate a warping analysis result.

[0038] In a third aspect, an embodiment of the present application provides a brightness compensation device based on step-by-step processing, comprising: a processor, a memory, an input-output unit, and a bus; the processor is connected to the memory, the input-output unit, and the bus; the memory stores a program, and the processor calls the program to execute the first aspect and any optional brightness compensation method of the first aspect.

[0039] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a program is stored. When the program is executed on a computer, the program performs the first aspect and any optional brightness compensation method of the first aspect.

[0040] It can be seen from the above technical solutions that the embodiments of the present application have the following advantages:

[0041] The present application first obtains N captured images of the display screen to be tested at different preset display grayscales, where N is an integer greater than or equal to 2. Next, the position data and brightness data of each pixel in each captured image are obtained. Then, the brightness compensation coefficients of all captured images are modeled to generate relationship matrix data, wherein the relationship matrix data includes brightness compensation coefficient matrix data, pixel position matrix data, and brightness order matrix data. The relationship matrix data is adjusted according to the brightness data, position data, and predetermined data order of each pixel in each captured image to generate a brightness compensation coefficient expression. The brightness transformation matrix corresponding to the brightness order matrix data in the brightness compensation coefficient expression is decomposed and optimized to generate a result matrix; the elements of the result matrix are sequentially generated into N*N coefficient images, and the value of each coefficient image is any element of the result matrix; the NxN coefficient images and the N captured images are processed step by step, and the coefficient images and the captured images are sequentially integrated for pixels at the same position in units of images according to the pixel position matrix to generate a brightness compensation coefficient; the brightness at each pixel is compensated using the brightness compensation coefficient.

[0042] By decomposing and optimizing the brightness transformation matrix corresponding to the brightness order matrix data in the brightness compensation coefficient expression, the least squares method is used for QR decomposition to obtain the corresponding result matrix, instead of directly solving the matrix in the original modeling. This method improves the numerical stability of brightness compensation and thus improves the brightness compensation efficiency of the new display screen. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments or descriptions of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0044] Figure 1 This is a schematic diagram of an embodiment of the brightness compensation method based on step-by-step processing of the present application;

[0045] Figure 2 A schematic diagram of an embodiment of a method for generating a brightness compensation coefficient according to the present application;

[0046] Figure 3 A schematic diagram of an embodiment of a method for generating a result matrix for this application;

[0047] Figure 4 A schematic diagram of an embodiment of a method for acquiring an image of a display screen to be tested according to the present application;

[0048] Figure 5 A schematic diagram of an embodiment of a method for treating warping defects in flexible splicing according to the present application;

[0049] Figure 6 A schematic diagram of an embodiment of a method for analyzing warping defects in a flexible splicing screen according to the present application;

[0050] Figure 7 This is a schematic diagram of an embodiment of a brightness compensation device based on step-by-step processing of the present application;

[0051] Figure 8 This is a schematic diagram of another embodiment of the brightness compensation device based on step-by-step processing of the present application;

[0052] Figure 9 This is a schematic diagram of another embodiment of the method for performing image preprocessing based on a captured image according to the present application;

[0053] Figure 10 This is a schematic diagram of another embodiment of the method for capturing display screen images according to the present application. DETAILED DESCRIPTION

[0054] In the following description, specific details such as specific system structures and techniques are provided for purposes of illustration rather than limitation to facilitate a thorough understanding of the embodiments of the present application. However, it will be apparent to those skilled in the art that the present application may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid obscuring the description of the present application with unnecessary detail.

[0055] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or collections thereof.

[0056] It will also be understood that the term "and / or" used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0057] As used in this specification and the appended claims, the term "if" can be interpreted as "when" or "upon" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "upon determination" or "in response to determining" or "upon detection of [described condition or event]" or "in response to detecting [described condition or event]," depending on the context.

[0058] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0059] References to "one embodiment" or "some embodiments" in this specification mean that a particular feature, structure, or characteristic described in conjunction with that embodiment is included in one or more embodiments of the present application. Thus, phrases such as "in one embodiment," "in some embodiments," "in other embodiments," and "in other embodiments" appearing in various places in this specification do not necessarily refer to the same embodiment, but rather mean "one or more but not all embodiments," unless otherwise specifically emphasized. The terms "including," "comprising," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0060] In the field of new display panels, current technologies for brightness compensation to address display mura (mura) primarily include global brightness adjustment and regional brightness correction. The brightness compensation algorithm (i.e., demura) adjusts the brightness of each pixel on a display. The relationship between brightness and each pixel is derived from multiple captured grayscale images, primarily through mathematical modeling. Brightness compensation for new displays typically requires cross-image mathematical modeling for the same pixel location across multiple images. To ensure effective brightness compensation, the grayscale images currently used for brightness compensation are typically high-resolution, typically 7680*4320. Directly calculating coefficients based on matrix operations requires constructing the pixel data for the same location across N images (with a resolution of m*n) into a three-dimensional matrix N*N*(m*n). Solving the coefficient vector pixel by pixel using the least-squares normal equations exponentially increases the amount of data and computationally intensive. This consumes significant memory resources, easily leading to memory shortages. Furthermore, the numerous matrix multiplications and inversion operations significantly increase computation time and lead to poor numerical stability, severely impacting the algorithm's real-time performance and practicality. Currently, GPU acceleration can also be achieved through CUDA / OpenCL, which can perform highly parallel computing acceleration processing on a pixel-by-pixel basis, but this is limited by video memory capacity, hardware parallel efficiency, algorithm adaptability, and programming complexity.

[0061] Based on this, the present application discloses a brightness compensation method, device and storage medium based on step-by-step processing, which are used to improve the brightness compensation efficiency of a new display screen.

[0062] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0063] The method of the present application can be applied to a server, device, terminal or other device with logic processing capability, and the present application does not limit this. For the convenience of description, the following description is based on the example of the execution subject being a terminal.

[0064] See also Figure 1 The present application provides an embodiment of a brightness compensation method based on step-by-step processing, comprising:

[0065] 101. Obtain N captured images of the display screen to be tested at different preset display grayscales, where N is an integer greater than or equal to 2.

[0066] In this embodiment, target images (sampling images) of the display panel at different preset display grayscales are acquired by an industrial-grade sampling camera.

[0067] 102. Obtain position data and brightness data of each pixel in each collected image.

[0068] After obtaining sample images of the display panel at different preset display grayscales through an industrial-grade sampling camera, the brightness data and position information corresponding to each pixel in the sample image of the target grayscale are obtained. Before obtaining the brightness data, due to factors such as camera lens distortion, noise and background area, the target image should be preprocessed, including but not limited to coordinate transformation, geometric correction, Gaussian filtering, etc., to avoid abnormal compensation effect. After preprocessing the sampled image, it is necessary to obtain the position data and brightness data of each pixel in each captured image. Next, it is necessary to fit the brightness compensation coefficients of multiple grayscale images step by step, and accumulate the results of the step-by-step fitting coefficients.

[0069] 103. Model the brightness compensation coefficients of all collected images to generate relationship matrix data, where the relationship matrix data includes brightness compensation coefficient matrix data, pixel position matrix data, and brightness order matrix data.

[0070] The terminal models the brightness compensation coefficients of all collected images and generates relationship matrix data, wherein the relationship matrix data includes brightness compensation coefficient matrix data, pixel position matrix data and brightness order matrix data.

[0071] Assume that N high-resolution (m*n) sampling images of different grayscales need to be taken, and the position of each pixel is , where i and j are the positions of the pixel coordinates respectively. Next, high-order modeling is performed to calculate the corresponding N brightness compensation coefficients. The compensation coefficient set is 、 to , brightness order matrix data , pixel position matrix data and brightness compensation coefficient matrix data As shown below:

[0072]

[0073]

[0074]

[0075] Then fit is performed, and the expression of the relationship matrix data is as follows:

[0076]

[0077]

[0078] in,

[0079] 104. Adjust the relationship matrix data according to the brightness data, position data and predetermined data order of each pixel point in each collected image to generate a brightness compensation coefficient expression.

[0080] The terminal adjusts the relationship matrix data according to the brightness data, position data and predetermined data order of each pixel in each captured image to generate a brightness compensation coefficient expression. Specifically, the terminal fits the final brightness compensation coefficient by solving the normal equations based on the least squares method. 、 to for:

[0081]

[0082] 105. Decompose and optimize the brightness transformation matrix corresponding to the brightness order matrix data in the brightness compensation coefficient expression to generate a result matrix.

[0083] After deriving the final brightness compensation coefficient, the brightness order matrix data of the parameters can be combined , pixel position matrix data Perform calculations.

[0084] At this time, if we directly combine the brightness order matrix data right Matrix inversion operations are prone to poor numerical stability due to the high precision and large number of pixels in linear displays. To improve numerical stability, a decomposition and optimization can be performed based on the brightness transformation matrix corresponding to the brightness order matrix data in the brightness compensation coefficient expression to generate a result matrix. The specific decomposition and optimization methods are described in the subsequent examples.

[0085] Then calculate the decomposed data The result matrix .

[0086] 106. Generate N*N coefficient images in sequence from the elements of the result matrix, where the value of each coefficient image is any element of the result matrix.

[0087] The terminal generates N*N coefficient images in sequence from the elements of the result matrix. The value of each coefficient image is any element of the result matrix. Specifically, the matrix The elements of are sequentially generated into NxN coefficient images REImage (1,1)~REImage (N,N) , at this time the image resolution is m*n, and the values ​​of each coefficient image are matrices Any element Re 1*1 ,Re 1*2 ,Re 1*3 ,...,Re (N-1)*(N-1) ,Re (N)*(N) .

[0088] 107. Process the NxN coefficient images and the N acquired images in steps, and integrate the coefficient images and the acquired images for pixels at the same position in units of images according to the pixel position matrix to generate brightness compensation coefficients.

[0089] The terminal processes NxN coefficient images and N acquired images in steps, and integrates the coefficient images and acquired images for pixels at the same position in units of images according to the pixel position matrix to generate brightness compensation coefficients. That is, a set of coefficient images and an acquired image are processed in steps, and then the next set of coefficient images and the next acquired image are used in turn to integrate the processed data of the previous set and finally generate brightness compensation coefficients.

[0090] 108. Use the brightness compensation coefficient to compensate the brightness of each pixel.

[0091] Finally, the terminal uses the brightness compensation coefficient to compensate the brightness of each pixel.

[0092] The present application first obtains N captured images of the display screen to be tested at different preset display grayscales, where N is an integer greater than or equal to 2. Next, the position data and brightness data of each pixel in each captured image are obtained. Then, the brightness compensation coefficients of all captured images are modeled to generate relationship matrix data, wherein the relationship matrix data includes brightness compensation coefficient matrix data, pixel position matrix data, and brightness order matrix data. The relationship matrix data is adjusted according to the brightness data, position data, and predetermined data order of each pixel in each captured image to generate a brightness compensation coefficient expression. The brightness transformation matrix corresponding to the brightness order matrix data in the brightness compensation coefficient expression is decomposed and optimized to generate a result matrix; the elements of the result matrix are sequentially generated into N*N coefficient images, and the value of each coefficient image is any element of the result matrix; the NxN coefficient images and the N captured images are processed step by step, and the coefficient images and the captured images are sequentially integrated for pixels at the same position in units of images according to the pixel position matrix to generate a brightness compensation coefficient; the brightness at each pixel is compensated using the brightness compensation coefficient.

[0093] By decomposing and optimizing the brightness transformation matrix corresponding to the brightness order matrix data in the brightness compensation coefficient expression, the least squares method is used for QR decomposition to obtain the corresponding result matrix, instead of directly solving the matrix in the original modeling. This method improves the numerical stability of brightness compensation and thus improves the brightness compensation efficiency of the new display screen.

[0094] See also Figure 2 The present application provides an embodiment of a method for generating a brightness compensation coefficient, comprising:

[0095] 201. Determine the coefficient image of the first row in the NxN coefficient images and the corresponding first acquired image, integrate the pixels at the same position according to the pixel position matrix and in units of images, and generate a first step processing result.

[0096] This embodiment proposes a brightness compensation method for performing step-by-step processing on multiple grayscale images, which can reduce memory usage, has low programming complexity, and is not limited by hardware conditions.

[0097] The terminal calculates the decomposition expression obtained by QR decomposition The result matrix , at this time the brightness compensation coefficient is:

[0098]

[0099] The terminal generates N*N coefficient images in sequence from the elements of the result matrix. The value of each coefficient image is any element of the result matrix. Specifically, the matrix The elements of are sequentially generated into NxN coefficient images REImage (1,1) ~REImage (N,N) , at this time the image resolution is m*n, and the values ​​of each coefficient image are matrices Any element Re 1*1 ,Re 1*2 ,Re 1*3 ,...,Re (N-1)*(N-1) ,Re (N)*(N) .

[0100] For NxN coefficient images REImage (1,1) ~REImage (N,N) And the grayscale images PixelImage1~PixelImage that need to be fitted N Multiply the pixels at the same position in units of images to obtain the first step processing result image CoefImage1, that is, the first step processing result, as shown below:

[0101]

[0102] Among them, i and j represent the position coordinates of the pixel points on the image, (1,1) and (1,2) are the coefficient matrices The element position, NxN coefficient image REImage (1,1) ~REImage (N,N) Reference coefficient matrix The coefficient image at the corresponding position in , namely ReImage （1，1） It refers to a constant image consisting of the elements in the first row and first column of the coefficient matrix ReNxN. CoefImage1 includes N corresponding data and is a set.

[0103] 202. Determine the coefficient image of the second row in the NxN coefficient images and the corresponding second acquired image, integrate the pixels at the same position according to the pixel position matrix and in units of images, and then combine the integration result with the first step processing result to generate a second step processing result.

[0104] Next, the second step processing is superimposed on the first step processing result image CoefImage1 to obtain the second step processing result image CoefImage2, that is:

[0105]

[0106] 203. Similarly, determine the coefficient image of the Nth row and the corresponding Nth acquired image, integrate the pixels at the same position according to the pixel position matrix and in units of images, and then combine the integration result with the N-1th step processing result to generate the target processing result.

[0107] By analogy, when the Nth step processing result is obtained, the specific result form of the fitting calculation coefficient FinalCoeflImage(N,i,j) of the pixels at the same position of the final multiple grayscale images is obtained:

[0108]

[0109] 204. Determine the target processing result as a brightness compensation coefficient.

[0110] Finally, the target processing result is presented. In the above solution, the terminal performs pixel-by-pixel fitting on the same pixel position in multiple high-resolution (m*n) grayscale images, PixelImage1 through PixelImageN. This is computationally intensive and significantly increases the computation time. Currently, GPUs and CUDA can be used for highly parallel accelerated processing, but this requires a deep understanding of the CUDA programming model. Furthermore, video memory usage increases linearly with the number of pixels, and data parallelism exacerbates memory management pressures.

[0111] Secondly, by calculating the corresponding brightness fitting coefficients for multiple grayscale images step by step on an image-by-image basis and then superimposing them to obtain the fitting coefficients corresponding to each pixel, the calculation of each single pixel can be avoided, which can further improve the brightness compensation efficiency of the new display screen.

[0112] See also Figure 3 , the present application provides an embodiment of a method for generating a result matrix, comprising:

[0113] 301. Decompose and optimize the brightness transformation matrix corresponding to the brightness order matrix data in the brightness compensation coefficient expression to generate an orthogonal data set and a triangular data set.

[0114] In this embodiment, the terminal decomposes and optimizes the brightness transformation matrix corresponding to the brightness order matrix data in the brightness compensation coefficient expression to generate an orthogonal data set and a triangular data set. Specifically, the QR decomposition method is used for auxiliary optimization to convert the brightness order matrix data (coefficient matrix) Decompose into orthogonal data sets and triangular (upper triangle) data sets , there are the following expressions:

[0115] .

[0116] The decomposition expression can be obtained by QR decomposition:

[0117]

[0118] Rather than directly targeting To solve the brightness compensation coefficient, the computational complexity of the QR decomposition method is reduced from O(N 3 ) is reduced to O(N 2 ), which can greatly improve the calculation speed and increase efficiency.

[0119] 302. Generate a result matrix according to the orthogonal decomposition data and the triangular decomposition data.

[0120] Calculation of the decomposition expression obtained by QR decomposition The result matrix , at this time the brightness compensation coefficient is:

[0121]

[0122] The result matrix generated in this way can better calculate the brightness compensation coefficient.

[0123] See also Figure 4 The present application provides an embodiment of a method for acquiring an image of a display screen to be tested, wherein the display screen to be tested is a display screen composed of several flexible spliced ​​screens, including:

[0124] 401. Combine the flexible spliced ​​display screens to form a display screen to be tested.

[0125] In this embodiment, the flexible splicing screen is a new type of display screen, which has the function of bendability and multi-piece assembly. It is different from the conventional splicing screen. The conventional splicing screen is a fixed block, and the curvature of the splicing screen needs to be designed in advance and then spliced ​​to form a large-scale curved screen. The flexible splicing screen of the present application can still be bent after splicing, and there will be no separation between the pixels of the splicing screen.

[0126] A fixed edge connection layer is added to a certain level within a traditional flexible display screen, allowing two flexible screens to be connected through the edge connection layer. The edge connection layer is located below the pixel layer to avoid affecting the display of the pixel layer of the display screen. However, there are certain problems with the existing edge connection layer. The edge connection layer is usually magnetically spliced ​​and interlocked, requiring a corresponding structure to be designed on the edge connection layer. This structure is relatively small, making it very prone to alignment errors during the splicing process. This error will cause further abnormalities in subsequent splicing, thereby generating warping defects. Warping defects can be divided into linear warping defects, which will cause linear raised warping on the flexible splicing screen and cause other flexible splicing screens (flexible splicing screens connected to it) to also cause linear warping. Another type of nonlinear warping defect is that at least two flexible splicing screens connected to it around the target flexible splicing screen are not aligned with the target flexible splicing screen, causing the target flexible splicing screen to be internally squeezed and generate irregular warping.

[0127] 402 , performing lighting processing on the display screen to be tested with different preset display grayscale images, lighting the central point area of ​​the display screen to be tested, and lighting the central pixel point of each flexible spliced ​​display screen.

[0128] The terminal illuminates the display under test at different preset grayscale levels, illuminating the center area of ​​the display under test and the center pixel of each flexible tiled display. This determines the overall center and the center of each tiled display. The center area can be in the middle of a single flexible tiled display or between four flexible tiled displays, without limitation.

[0129] 403 : Adjust the position of the sampling camera so that the sampling center of the sampling camera is aligned with the center point of the central point area, and capture the first image to be adjusted at the center point of the central point area through the sampling camera.

[0130] The terminal adjusts the position of the sampling camera so that the sampling center of the sampling camera is aligned with the center point of the central point area, and collects the first image to be adjusted at the center point of the central point area through the sampling camera.

[0131] 404 : Perform a warping analysis on the display screen to be tested according to the position coordinates of the central point area in the first image to be adjusted, the coordinate information and the grayscale information of the central pixel point of each flexible spliced ​​display screen.

[0132] The terminal first performs a preliminary detection based on the position coordinates of the center point area and the coordinate information of the center pixel of each flexible spliced ​​display screen, and then performs further detection using the grayscale information. The specific analysis steps are described in the subsequent embodiments.

[0133] 405. When the warpage analysis result shows that there is no flexible splicing warpage defect, the display screen to be tested is illuminated with different preset display grayscale images, and is captured by a sampling camera to generate a captured image.

[0134] When the warping analysis results show that there is no flexible splicing warping defect, the display screen to be tested is illuminated with different preset display grayscale images, that is, a uniform grayscale image of the area with no center point lighting is input, and the image is collected by the sampling camera to generate the corresponding collected image.

[0135] See also Figure 5 The present application provides an embodiment of a method for processing flexible splicing warping defects, comprising:

[0136] 501. When the warping analysis result shows that there is a flexible splicing warping defect, the flexible splicing screen with the flexible splicing warping defect is replaced according to the warping analysis result.

[0137] 502. Capture images of the replaced display screen to be tested again until the flexible splicing warping defect no longer exists, and recapture images using a sampling camera to generate captured images.

[0138] If the warpage analysis results indicate a flexible splicing warpage defect, the terminal will replace the flexible splicing screen with the defect based on the warpage analysis results. The terminal will then recapture images of the replaced display screen until the flexible splicing warpage defect is eliminated. The sampling camera will then recapture images to generate captured images.

[0139] See also Figure 6 The present application provides an embodiment of a method for analyzing warping defects of a flexible splicing screen, comprising:

[0140] 601. Expand the points of the spliced ​​screen according to the position coordinates of the central point area in the first image to be adjusted, and generate a reference midpoint on each flexible spliced ​​screen area.

[0141] In this embodiment, the splicing screen points are first expanded according to the position coordinates of the center point area in the first image to be adjusted, and a reference midpoint is generated on each flexible splicing screen area. That is, based on a standard screen without warping defects as a reference, the position that the center point of each flexible splicing screen should reach is set.

[0142] 602. Perform collective orientation deviation analysis on the coordinate information of the central pixel point of each flexible spliced ​​display screen on the first image to be adjusted and the reference midpoint.

[0143] Next, the terminal uses the center point of the center point area as a reference to perform a directional deviation analysis on the coordinate information of the reference midpoint and the detected central pixel point on each flexible splicing screen area. Specifically, the center point of the center point area is connected to the reference midpoint of each flexible splicing screen, and the straight line is used as the detection direction of the position deviation. Then, the coordinate information of the central pixel point detected by each flexible splicing screen is calculated by distance and direction calculation with the corresponding reference straight line to generate a first distance direction and a first vertical distance.

[0144] Then, the direction and distance of the detected coordinate information of the central pixel point and its corresponding reference midpoint are analyzed to generate a second direction and a second distance.

[0145] The linear deviation of each flexible video wall is generated based on the first distance direction and the first perpendicular distance. The nonlinear deviation is then generated based on the second direction and the second distance. Nonlinear warping can affect the display of the center area of ​​the flexible video wall. This can cause pixels to be farther from the sampling camera than other pixels, closer to the sampling camera, or even have their lighting direction misaligned with the sampling camera. Therefore, the second direction and the second distance must be analyzed.

[0146] The linear deviation and nonlinear deviation of a central pixel and its surrounding central pixel points are analyzed to determine the possibility of warping defects in the corresponding flexible splicing screen.

[0147] 603. When the analysis result shows that a warping defect exists, determine a warping defect area on the first image to be adjusted according to the collective orientation deviation analysis result, where the warping defect area consists of at least one flexible spliced ​​display screen area.

[0148] If the analysis results indicate a warping defect, this is only a preliminary determination of its presence and further testing is required. Based on the collective orientation deviation analysis results, the terminal determines the area of ​​the first image to be adjusted where the warping defect may exist (i.e., at least one flexible tiled screen with a warping defect). The warping defect area consists of at least one flexible tiled display area.

[0149] 604. Generate a plurality of grayscale gradient images based on the warping defect direction information of the collective directional deviation analysis result and a preset gradient degree, where the gradient degree is determined by the size of the flexible splicing screen.

[0150] The terminal generates several grayscale gradient images based on the warp defect direction information from the collective directional deviation analysis results and the preset gradient degree. The gradient degree is determined by the size of the flexible video wall. First, the terminal generates a grayscale range for linear warp defects and a grayscale range for nonlinear warp based on the possible warp types. The gradient degree is then set based on the size of the flexible video wall. The gradient direction is then set based on the orientation of the flexible video wall with respect to the center point, generating the corresponding grayscale gradient images.

[0151] 605. Perform grayscale gradient lighting processing on the flexible spliced ​​screen corresponding to the warping defect area.

[0152] Next, the terminal lights up the grayscale gradient image on the flexible splicing screen corresponding to the warping defect area.

[0153] 606. Adjust the position of the sampling camera so that the sampling center of the sampling camera is aligned with the center point of the flexible splicing screen, and collect a warping defect detection image through the sampling camera.

[0154] The terminal adjusts the position of the sampling camera so that the sampling center of the sampling camera is aligned with the center point of the flexible splicing screen, and collects warping defect detection images through the sampling camera. Such warping defect detection images can specifically detect different types of warping defects.

[0155] 607. Perform a warping grayscale gradient analysis on the warping defect detection image to generate a warping analysis result.

[0156] The terminal performs a warping grayscale gradient analysis on the warping defect detection image to generate a warping analysis result. Specifically, the gradient analysis is performed based on the line connecting the center points of the flexible splicing screen and the center area of ​​the screen to be detected as the direction, and then determines whether the gradient has distortion that causes a warping defect.

[0157] See also Figure 9 The present application provides an embodiment of a method for collecting images and performing image preprocessing, comprising:

[0158] 901. Perform image preprocessing on the N captured images. The image preprocessing is used to eliminate lens distortion, noise, and redundant background areas.

[0159] In this embodiment, before obtaining the brightness data, due to factors such as camera lens distortion, noise and background area, the target image should be preprocessed, including but not limited to coordinate transformation, geometric correction, Gaussian filtering, etc., to avoid abnormal compensation effect.

[0160] See also Figure 10 , the present application provides an embodiment of a method for capturing a display screen image, comprising:

[0161] 1001. Light up the display screen to be tested with different preset grayscale images, and light up the center area of ​​the display screen to be tested;

[0162] 1002. Adjust the position of the sampling camera so that the sampling center of the sampling camera is aligned with the center point of the display screen to be tested;

[0163] 1003. Capture an image at the center point of the center point area using a sampling camera to generate a captured image.

[0164] In this embodiment, when the display screen is a conventional display screen, warping analysis can be omitted and data acquisition can be performed directly. The terminal lights up the display screen to be tested with different preset display grayscale images, lights up the center point area of ​​the display screen to be tested, and then adjusts the position of the sampling camera so that the sampling center of the sampling camera is aligned with the center point of the display screen to be tested. Finally, the sampling camera is used to capture an image at the center point of the center point area to generate a captured image.

[0165] See also Figure 7 The present application provides an embodiment of a brightness compensation device based on step-by-step processing, comprising:

[0166] The first acquiring unit 701 is configured to acquire N captured images of the display screen to be tested at different preset display grayscales, where N is an integer greater than or equal to 2.

[0167] Optionally, the display screen to be tested is a display screen composed of several flexible spliced ​​screens.

[0168] The first acquiring unit 701 includes:

[0169] The splicing module 7011 is used to combine the flexible splicing display screens to form a display screen to be tested.

[0170] The first lighting module 7012 is used to perform lighting processing on the display screen to be tested with different preset display grayscale images, light up the central point area of ​​the display screen to be tested, and light up the central pixel point of each flexible spliced ​​display screen.

[0171] The first acquisition module 7013 is used to adjust the position of the sampling camera so that the sampling center of the sampling camera is aligned with the center point of the central point area, and acquire the first image to be adjusted at the center point of the central point area through the sampling camera.

[0172] The analysis module 7014 is configured to perform a warping analysis on the display screen to be tested based on the position coordinates of the center point area in the first image to be adjusted, the coordinate information and grayscale information of the center pixel point of each flexible spliced ​​display screen.

[0173] Optionally, the analysis module 7014 includes:

[0174] The splicing screen points are expanded according to the position coordinates of the central point area in the first image to be adjusted, and a reference midpoint is generated on each flexible splicing screen area.

[0175] A collective orientation deviation analysis is performed on the coordinate information of the central pixel point of each flexible spliced ​​display screen on the first image to be adjusted and the reference midpoint.

[0176] When the analysis result shows that a warping defect exists, a warping defect area on the first image to be adjusted is determined according to the collective orientation deviation analysis result, and the warping defect area consists of at least one flexible spliced ​​display screen area.

[0177] According to the warping defect direction information of the collective directional deviation analysis results and the preset gradient degree, several grayscale gradient images are generated. The gradient degree is determined by the size of the flexible splicing screen.

[0178] A grayscale gradient image is lit on the flexible splicing screen corresponding to the warping defect area.

[0179] Adjust the position of the sampling camera so that the sampling center of the sampling camera is aligned with the center point of the flexible splicing screen, and use the sampling camera to collect warping defect detection images.

[0180] Perform warping grayscale gradient analysis on the warping defect detection image to generate the warping analysis results.

[0181] The replacement module 7015 is configured to replace the flexible splicing screen having the warping defect according to the warping analysis result when the warping analysis result shows that the flexible splicing warping defect exists.

[0182] The generating module 7016 is used to collect images of the replaced display screen to be tested again until there is no flexible splicing warping defect, and re-collect images through the sampling camera to generate collected images.

[0183] The second acquisition module 7017 is used to light up the display screen to be tested with different preset display grayscale images when the warpage analysis result shows that there is no flexible splicing warpage defect, and to acquire images through a sampling camera to generate acquired images.

[0184] The second acquiring unit 702 is configured to acquire position data and brightness data of each pixel in each captured image.

[0185] The first generating unit 703 is configured to model the brightness compensation coefficients of all collected images and generate relationship matrix data, where the relationship matrix data includes brightness compensation coefficient matrix data, pixel position matrix data, and brightness order matrix data.

[0186] The second generating unit 704 is configured to adjust the relationship matrix data according to the brightness data, position data and predetermined data order of each pixel point in each captured image to generate a brightness compensation coefficient expression.

[0187] The third generating unit 705 is configured to perform decomposition and optimization on the brightness transformation matrix corresponding to the brightness order matrix data in the brightness compensation coefficient expression to generate a result matrix.

[0188] Optionally, the step of generating the result matrix by the third generating unit 705 includes:

[0189] The brightness transformation matrix corresponding to the brightness order matrix data in the brightness compensation coefficient expression is decomposed and optimized to generate an orthogonal data set and a triangular data set.

[0190] Generates a result matrix based on the orthogonal decomposition data and the triangular decomposition data.

[0191] The fourth generating unit 706 is configured to sequentially generate N*N coefficient images from the elements of the result matrix, where the value of each coefficient image is any element of the result matrix.

[0192] The fifth generating unit 707 is used to process the NxN coefficient images and the N acquired images in steps, and integrate the coefficient images and the acquired images for pixels at the same position in units of images according to the pixel position matrix to generate brightness compensation coefficients.

[0193] Optionally, the fifth generating unit 707 includes:

[0194] Determine the coefficient image of the first row in the NxN coefficient images and the corresponding first acquisition image, integrate the pixels at the same position according to the pixel position matrix and in units of images, and generate a first step processing result.

[0195] Determine the coefficient image of the second row in the NxN coefficient images and the corresponding second acquired image, integrate the pixels at the same position according to the pixel position matrix and in units of images, and then combine the integration result with the first step processing result to generate a second step processing result.

[0196] Similarly, determine the coefficient image of the Nth row and the corresponding Nth acquired image, integrate the pixels at the same position according to the pixel position matrix and in units of images, and then combine the integration result with the N-1th step processing result to generate the target processing result.

[0197] The target processing result is determined as a brightness compensation coefficient.

[0198] The compensation unit 708 is configured to compensate the brightness of each pixel using a brightness compensation coefficient.

[0199] See also Figure 8 , the present application provides a brightness compensation device based on step-by-step processing, comprising:

[0200] Processor 801 , memory 802 , input / output unit 803 , and bus 804 .

[0201] The processor 801 is connected to the memory 802 , the input and output unit 803 , and the bus 804 .

[0202] The memory 802 stores a program, and the processor 801 calls the program to execute the following Figure 1 、 Figure 2 and Figure 3 、 Figure 4 、 Figure 5 、 Figure 6 、 Figure 9 and Figure 10 Brightness compensation method in .

[0203] The present application provides a computer-readable storage medium, wherein a program is stored on the computer-readable storage medium, and when the program is executed on a computer, the program performs the following operations: Figure 1 、 Figure 2 and Figure 3 、 Figure 4 、 Figure 5 、 Figure 6 、 Figure 9 and Figure 10 Brightness compensation method in .

[0204] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0205] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0206] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across 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 application.

[0207] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0208] 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 computer-readable storage medium. Based on this understanding, the technical solution of the present application, 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 and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, read-only memory), random access memory (RAM, random access memory), disk or optical disk, and other media that can store program code.

Claims

1. A brightness compensation method based on step-by-step processing, characterized in that: include: Obtain N captured images of the display screen to be tested at different preset display grayscales, where N is an integer greater than or equal to 2; Obtain the position data and brightness data of each pixel in each collected image; Modeling the brightness compensation coefficients of all collected images to generate relationship matrix data, wherein the relationship matrix data includes brightness compensation coefficient matrix data, pixel position matrix data, and brightness order matrix data; Adjusting the relationship matrix data according to the brightness data, position data and predetermined data order of each pixel in each collected image to generate a brightness compensation coefficient expression; Decomposing and optimizing the brightness transformation matrix corresponding to the brightness order matrix data in the brightness compensation coefficient expression to generate a result matrix; Generate NxN coefficient images in sequence from the elements of the result matrix, where the value of each coefficient image is any element of the result matrix; Processing the NxN coefficient images and the N collected images in steps, integrating the coefficient images and the collected images for pixels at the same position in units of images according to the pixel position matrix, and generating brightness compensation coefficients; The brightness compensation coefficient is used to compensate the brightness of each pixel.

2. The brightness compensation method according to claim 1, wherein: The step of decomposing and optimizing the brightness transformation matrix corresponding to the brightness order matrix data in the brightness compensation coefficient expression to generate a result matrix includes: The QR decomposition method is used to decompose and optimize the brightness transformation matrix corresponding to the brightness order matrix data in the brightness compensation coefficient expression to generate a result matrix.

3. The brightness compensation method according to claim 2, wherein: The step of using the QR decomposition method to decompose and optimize the brightness transformation matrix corresponding to the brightness order matrix data in the brightness compensation coefficient expression to generate a result matrix includes: Performing QR decomposition optimization on the brightness transformation matrix corresponding to the brightness order matrix data in the brightness compensation coefficient expression to generate an orthogonal data set and a triangular data set; Generates a result matrix based on the orthogonal decomposition data and the triangular decomposition data.

4. The brightness compensation method according to claim 2, wherein: The step of processing the NxN coefficient images and the N acquired images in steps, integrating the coefficient images and the acquired images for pixels at the same position in units of images according to the pixel position matrix, and generating brightness compensation coefficients includes: Determine the coefficient image of the first row in the NxN coefficient images and the corresponding first acquired image, and integrate the pixels at the same position in units of images according to the pixel position matrix to generate a first step processing result; Determine the coefficient image of the second row in the NxN coefficient images and the corresponding second acquired image, integrate the pixels at the same position in units of images according to the pixel position matrix, and combine the integration result with the first step processing result to generate a second step processing result; Similarly, the coefficient image of the Nth row and the corresponding Nth acquired image are determined, the pixel points at the same position are integrated according to the pixel position matrix and in units of images, and the integration result is combined with the N-1th step processing result to generate the target processing result; The target processing result is determined as a brightness compensation coefficient.

5. The brightness compensation method according to claim 1, wherein: After the steps of acquiring N captured images of the display screen to be tested at different preset display grayscales, and acquiring position data and brightness data of each pixel in each captured image, the brightness compensation method further includes: The N captured images are subjected to image preprocessing, wherein the image preprocessing is used to eliminate lens distortion, noise, and redundant background areas.

6. The brightness compensation method according to any one of claims 1 to 5, characterized in that: The step of obtaining N captured images of the display screen to be tested at different preset display grayscales includes: Lighting up the display screen to be tested with different preset display grayscale images, and lighting up the central point area of ​​the display screen to be tested; Adjusting the position of the sampling camera so that the sampling center of the sampling camera is aligned with the center point of the display screen to be tested; The sampling camera collects an image at the center point of the center point area to generate a collected image.

7. The brightness compensation method according to any one of claims 1 to 5, characterized in that: The display screen to be tested is a display screen composed of several flexible spliced ​​screens; The step of obtaining N captured images of the display screen to be tested at different preset display grayscales includes: Combine the flexible spliced ​​display screens to form a display screen to be tested; Lighting up the display screen to be tested with different preset display grayscale images, lighting up the central point area of ​​the display screen to be tested, and lighting up the central pixel point of each flexible spliced ​​display screen; Adjusting the position of the sampling camera so that the sampling center of the sampling camera is aligned with the center point of the central point area, and collecting the first image to be adjusted at the center point of the central point area by the sampling camera; Performing a warping analysis on the display screen to be tested according to the position coordinates of the center point area in the first image to be adjusted, the coordinate information and grayscale information of the center pixel point of each flexible spliced ​​display screen; When the warping analysis result shows that there is no flexible splicing warping defect, the display screen to be tested is illuminated with different preset display grayscale images, and a sampling camera is used to capture images to generate captured images; When the warping analysis result shows that there is a flexible splicing warping defect, the flexible splicing screen with the flexible splicing warping defect is replaced according to the warping analysis result; The replaced display screen to be tested is imaged again until the flexible splicing warping defect no longer exists, and the image is recaptured by the sampling camera to generate an image.

8. A brightness compensation device based on step-by-step processing, characterized in that: include: The first acquisition unit is configured to acquire N captured images of the display screen to be tested at different preset display grayscales, where N is an integer greater than or equal to 2; A second acquisition unit is used to acquire position data and brightness data of each pixel in each collected image; A first generating unit is configured to model the brightness compensation coefficients of all collected images and generate relationship matrix data, wherein the relationship matrix data includes brightness compensation coefficient matrix data, pixel position matrix data, and brightness order matrix data; A second generating unit is configured to adjust the relationship matrix data according to the brightness data, position data and a predetermined data order of each pixel point in each collected image to generate a brightness compensation coefficient expression; a third generating unit, configured to perform decomposition and optimization on the brightness transformation matrix corresponding to the brightness order matrix data in the brightness compensation coefficient expression to generate a result matrix; a fourth generating unit, configured to sequentially generate NxN coefficient images from the elements of the result matrix, wherein the value of each coefficient image is any element of the result matrix; a fifth generating unit, configured to process the NxN coefficient images and the N collected images in steps, and integrate the coefficient images and the collected images for pixels at the same position in units of images according to the pixel position matrix to generate brightness compensation coefficients; The compensation unit is configured to compensate the brightness of each pixel using the brightness compensation coefficient.

9. The brightness compensation device according to claim 8, characterized in that: The third generating unit includes: Decomposing and optimizing the brightness transformation matrix corresponding to the brightness order matrix data in the brightness compensation coefficient expression to generate an orthogonal data set and a triangular data set; Generates a result matrix based on the orthogonal decomposition data and the triangular decomposition data.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a program, and when the program is executed on a computer, the brightness compensation method according to any one of claims 1 to 7 is executed.

Images