A method, device, system and storage medium for display screen flat field correction

Abstract

The present application discloses a method, device, system and storage medium for flat field correction of a display screen, which is used to improve the uniformity of the display screen image after flat field correction. The initial bright field images of several frames are collected by an acquisition device; grayscale averaging is performed on the initial bright field images of the several frames to generate an average bright field image; an ROI area is selected on the average bright field image according to the grayscale uniformity of the average bright field image; the ROI area mean is generated according to the pixel point information of the ROI area; a flat field correction coefficient map is generated according to the average bright field image and the ROI area mean; the display screen to be corrected is collected by the acquisition device, and the collected image to be corrected is flat field corrected according to the flat field correction coefficient map.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of display screen detection, and in particular to a method, device, system and storage medium for display screen flat field correction. Background Art

[0002] With the rapid development of industrial and Internet technologies, the industry's requirements for industrial product quality are becoming more and more refined and standardized. As far as the display panel industry is concerned, the quality of products directly affects its product competitiveness. Among them, the accuracy of product shape and size specifications is the most basic process indicator of product quality. As one of the display components of the device, the display screen is used in various high-end devices, such as mobile phones, TVs, tablets, etc. As people's requirements for screen display continue to increase, the display screen has gradually become a technologically sophisticated product.

[0003] With the update and iteration of electronic products, display screens are used more frequently, and consumers have higher requirements for product quality. This has led to an increase in the content of display screen inspections and an increase in the accuracy of inspections. After using the acquisition equipment to collect the display screen to be tested, multiple preprocessing is often required so that the collected image can reflect the display of the actual display screen to be tested as much as possible, because the display screen usually needs to input calibration images of different grayscales and different types, and different calibration images will make the display effect of each pixel different. Flat field correction is an important part of display screen image preprocessing, because display screen image acquisition usually needs to be carried out in a dark room in order to avoid noise caused by other visible light, but in dark surrounding conditions, the grayscale will be lower. If flat field correction is not performed, the accuracy of the display screen image grayscale conversion to color will be greatly reduced.

[0004] The purpose of flat field correction for display screen images is to eliminate the unevenness in display screen images, making the brightness distribution of display screen images more uniform, thereby improving the quality and accuracy of the image. Solutions of existing technologies: Existing display screen image flat field correction technologies mainly include hardware correction and software correction. Hardware correction mainly eliminates the unevenness of display screen images by improving the hardware design of display screen imaging equipment, such as: using better lenses, higher sensor sensitivity, etc. Software correction eliminates image unevenness through image processing algorithms, such as histogram equalization, contrast stretching, etc.

[0005] However, in the prior art, display screen products are updated and iterated very quickly, but the acquisition equipment (sensors and lenses) is expensive and requires complex debugging. As the display screen is continuously updated and iterated, the hardware correction will reduce its correction effect. In addition, during the continuous use of the hardware, unstable factors such as bad pixels and jitter will appear on the sensor. These will greatly affect the effect of the display screen image during the software correction process, thereby reducing the effect of the flat field correction of the display screen image, and further causing the uniformity of the display screen image to decrease. Summary of the invention

[0006] The present application discloses a method, device, system and storage medium for flat field correction of a display screen, which are used to improve the uniformity of a display screen image after flat field correction.

[0007] The first aspect of the present application discloses a method for flat field correction of a display screen, comprising:

[0008] Collecting a number of frames of initial bright field images by using an acquisition device;

[0009] Perform grayscale averaging processing on the initial bright field images of several frames to generate an average bright field image;

[0010] Select the ROI area on the average bright field image according to the gray uniformity of the average bright field image;

[0011] Generate the ROI area mean value according to the pixel point information of the ROI area;

[0012] Generate a flat field correction coefficient map based on the average bright field image and the ROI area mean;

[0013] The display screen to be corrected is collected by an acquisition device, and a flat field correction process is performed on the collected image to be corrected according to the flat field correction coefficient map.

[0014] Optionally, a plurality of frames of initial bright field images are collected by a collection device, including:

[0015] Set the lighting parameters of the spherical integral light source, and light up the spherical integral light source under the acquisition device according to the lighting parameters;

[0016] The spherical integral light source is collected by an acquisition device to generate several frames of bright field images.

[0017] Optionally, selecting a ROI region on the average bright field image according to the grayscale uniformity of the average bright field image includes:

[0018] The average bright field image is divided into blocks to generate a bright field central area and a plurality of hierarchical block areas, wherein the hierarchical block areas are areas generated by hierarchical block generation from the bright field central area layer by layer outward;

[0019] Determine the coordinate set of the bad points in the bright field center area and the hierarchical block area;

[0020] Repairing the bad points in the bad point coordinate set by using the initial bright field images of several frames;

[0021] The uniformity level analysis is performed based on the grayscale values ​​of the pixels in the bright field center area and the hierarchical block area;

[0022] A ROI region is generated on the average bright field image according to the uniformity level analysis result and the resolution information of the average bright field image.

[0023] Optionally, the average bright field image is processed into blocks to generate a bright field center area and hierarchical block areas, including:

[0024] Mark the central area of ​​the spherical integrated light source on the average bright field image;

[0025] The average bright field image is divided into blocks according to the central area, and the grayscale mean value of each block is calculated;

[0026] Determine a set of block regions whose grayscale mean value on the average bright field image reaches the grayscale threshold range of the spherical integrated light source;

[0027] Perform regional distribution analysis and grayscale center analysis on each qualified block area in the block area set, and determine the bright field center coordinates based on the regional distribution analysis results and the grayscale center analysis results;

[0028] A bright field center area is generated with the bright field center coordinates as the center, and hierarchical blocks are performed layer by layer from the bright field center area outward to generate hierarchical block areas on the average bright field image.

[0029] Optionally, repairing the bad pixels in the bad pixel coordinate set is performed using a plurality of frames of initial bright field images, including:

[0030] An initial auxiliary repair area is generated on the initial bright field images of several frames with the bad point coordinates as the center;

[0031] Calculate the attention value of normal pixels in the initial auxiliary restoration area of ​​each initial bright field image;

[0032] Grayscale fusion is performed according to the attention value and grayscale value of normal pixels in each initial auxiliary repair area to generate a target auxiliary repair area. The number of pixels in the target auxiliary repair area is the same as that in the initial auxiliary repair area.

[0033] The bad pixels are repaired according to the grayscale values ​​of the pixels in the target auxiliary repair area, so that all the bad pixels in the bad pixel coordinate set are repaired.

[0034] Optionally, uniformity level analysis is performed based on the grayscale values ​​of pixels in the bright field center area and several hierarchical block areas, including:

[0035] Calculate the bright field center grayscale mean of the bright field center area;

[0036] Calculate the level grayscale mean set of each level block area;

[0037] Perform pixel partitioning on each hierarchical block area to generate partitioned pixels, and the number of pixels in each partitioned pixel area is the same;

[0038] Calculate the grayscale mean for each partition pixel area in each level block area to generate a partition grayscale value set;

[0039] Generate a first uniformity parameter for each hierarchical block area according to the bright field center grayscale mean and the hierarchical grayscale mean set;

[0040] Determine the subarea pixel point area that meets the uniformity standard according to the bright field center grayscale mean and the subarea grayscale value set;

[0041] Generate a second uniformity parameter for each hierarchical block area according to the partitioned pixel point area that meets the uniformity standard;

[0042] The uniformity level of each hierarchical block area is determined according to the first uniformity parameter and the second uniformity parameter.

[0043] Optionally, a flat field correction coefficient map is generated based on the average bright field image and the ROI area mean, including:

[0044] The pixel value of the pixel on the average bright field image is divided by the mean value of the ROI area to generate a flat field correction coefficient map.

[0045] The second aspect of the present application discloses a device for flat field correction of a display screen, comprising:

[0046] An acquisition unit, used for acquiring a plurality of frames of initial bright field images through an acquisition device;

[0047] A first generating unit is used to perform grayscale averaging processing on a plurality of frames of initial bright field images to generate an average bright field image;

[0048] A selection unit, used for selecting a ROI area on the average bright field image according to the grayscale uniformity of the average bright field image;

[0049] A second generating unit, used for generating a ROI area mean value according to pixel point information of the ROI area;

[0050] A third generating unit is used to generate a flat field correction coefficient map according to the average bright field image and the ROI area mean;

[0051] The flat field correction unit is used to collect the display screen to be corrected through the collection device, and perform flat field correction processing on the collected image to be corrected according to the flat field correction coefficient map.

[0052] Optional, acquisition unit, including:

[0053] Set the lighting parameters of the spherical integral light source, and light up the spherical integral light source under the acquisition device according to the lighting parameters;

[0054] The spherical integral light source is collected by an acquisition device to generate several frames of bright field images.

[0055] Optionally, select units, including:

[0056] A block division module is used to divide the average bright field image into blocks to generate a bright field central area and a plurality of hierarchical block areas, wherein the hierarchical block areas are areas generated by hierarchical block generation from the bright field central area layer by layer outward;

[0057] A determination module, used to determine a set of bad point coordinates in a bright field center area and a hierarchical block area;

[0058] A repair module, used for repairing bad points in a bad point coordinate set by using a plurality of frames of initial bright field images;

[0059] An analysis module is used to perform uniformity level analysis based on the grayscale values ​​of pixels in the bright field center area and the hierarchical block area;

[0060] The generating module is used to generate a ROI area on the average bright field image according to the uniformity level analysis result and the resolution information of the average bright field image.

[0061] Optional, block modules, including:

[0062] Mark the central area of ​​the spherical integrated light source on the average bright field image;

[0063] The average bright field image is divided into blocks according to the central area, and the grayscale mean value of each block is calculated;

[0064] Determine a set of block regions whose grayscale mean value on the average bright field image reaches the grayscale threshold range of the spherical integrated light source;

[0065] Perform regional distribution analysis and grayscale center analysis on each qualified block area in the block area set, and determine the bright field center coordinates based on the regional distribution analysis results and the grayscale center analysis results;

[0066] A bright field center area is generated with the bright field center coordinates as the center, and hierarchical blocks are performed layer by layer from the bright field center area outward to generate hierarchical block areas on the average bright field image.

[0067] Optional, repair module, including:

[0068] An initial auxiliary repair area is generated on the initial bright field images of several frames with the bad point coordinates as the center;

[0069] Calculate the attention value of normal pixels in the initial auxiliary restoration area of ​​each initial bright field image;

[0070] Grayscale fusion is performed according to the attention value and grayscale value of normal pixels in each initial auxiliary repair area to generate a target auxiliary repair area. The number of pixels in the target auxiliary repair area is the same as that in the initial auxiliary repair area.

[0071] The bad pixels are repaired according to the grayscale values ​​of the pixels in the target auxiliary repair area, so that all the bad pixels in the bad pixel coordinate set are repaired.

[0072] Optional, analysis modules, including:

[0073] Calculate the bright field center grayscale mean of the bright field center area;

[0074] Calculate the level grayscale mean set of each level block area;

[0075] Perform pixel partitioning on each hierarchical block area to generate partitioned pixels, and the number of pixels in each partitioned pixel area is the same;

[0076] Calculate the grayscale mean for each partition pixel area in each level block area to generate a partition grayscale value set;

[0077] Generate a first uniformity parameter for each hierarchical block area according to the bright field center grayscale mean and the hierarchical grayscale mean set;

[0078] Determine the subarea pixel point area that meets the uniformity standard according to the bright field center grayscale mean and the subarea grayscale value set;

[0079] Generate a second uniformity parameter for each hierarchical block area according to the partitioned pixel point area that meets the uniformity standard;

[0080] The uniformity level of each hierarchical block area is determined according to the first uniformity parameter and the second uniformity parameter.

[0081] Optionally, the third generation unit includes:

[0082] The pixel value of the pixel on the average bright field image is divided by the mean value of the ROI area to generate a flat field correction coefficient map.

[0083] The third aspect of the present application provides a system for display screen flat field correction, comprising:

[0084] Processor, memory, input-output unit, and bus;

[0085] The processor is connected to the memory, the input and output unit, and the bus;

[0086] The memory stores a program, and the processor calls the program to execute the first aspect and any optional method of the first aspect.

[0087] A fourth aspect 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 executes the first aspect and any optional method of the first aspect.

[0088] It can be seen from the above technical solutions that the embodiments of the present application have the following advantages:

[0089] In this application, first, several frames of initial bright field images are collected by an acquisition device. Then, the initial bright field images of several frames are subjected to grayscale averaging to generate an average bright field image. Multi-needle averaging can eliminate many random noises and system errors generated in the detection environment. Next, the ROI area is selected on the average bright field image according to the grayscale uniformity of the average bright field image, and the area with uniformity that meets the standard under different grayscales is determined, which is used as a reference area. The ROI area mean is generated according to the pixel point information of the ROI area. Then, a flat field correction coefficient map is generated according to the average bright field image and the ROI area mean. The flat field correction coefficient map has the flat field correction coefficient of the acquisition device on each pixel. Finally, the display screen to be corrected is collected by the acquisition device, and the pixels on the collected image to be corrected are flat-field corrected one by one according to the flat field correction coefficient map.

[0090] In this solution, the ROI area with uniformity that meets the standard is used as the reference area, the ROI area mean is calculated, and then the flat field correction coefficient map is generated based on the average bright field image and the ROI area mean, which can effectively reduce the problem of decreased correction effect caused by unstable factors such as bad pixels and jitter in the acquisition device sensor. Specifically, the flat field correction coefficient map is calculated using a high-precision floating point type (ROI area mean), which can obtain a more accurate flat field correction coefficient map, effectively eliminate the unevenness in the display image, and effectively improve the flat field correction effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0091] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. 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 paying creative labor.

[0092] Figure 1 A schematic diagram of an embodiment of a method for flat field correction of a display screen according to the present application;

[0093] Figure 2 A schematic diagram of an embodiment of a method for generating an initial bright field image for the present application;

[0094] Figure 3 A schematic diagram of an embodiment of a method for selecting a ROI region according to grayscale uniformity in the present application;

[0095] Figure 4 A schematic diagram of an embodiment of the method for processing average bright field images by blocks in the present application;

[0096] Figure 5 A schematic diagram of another embodiment of the method for repairing a sensor bad pixel on a bright field image of the present application;

[0097] Figure 6 A schematic diagram of an embodiment of the method for uniformity level analysis of the present application;

[0098] Figure 7 A schematic diagram of an embodiment of a method for generating a flat field correction coefficient map for the present application;

[0099] Figure 8 A schematic diagram of an embodiment of a device for flat field correction of a display screen according to the present application;

[0100] Fig. 9 A schematic diagram of an embodiment of a system for flat-field correction of a display screen according to the present application. DETAILED DESCRIPTION

[0101] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also 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 prevent unnecessary details from obstructing the description of the present application.

[0102] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, wholes, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or combinations thereof.

[0103] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0104] As used in the specification and appended claims of this application, the term "if" can be interpreted as "when" or "uponce" 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 "uponce it is determined" or "in response to determining" or "uponce [described condition or event] is detected" or "in response to detecting [described condition or event]", depending on the context.

[0105] 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.

[0106] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0107] In the prior art, display screen products are updated and iterated very quickly, but the acquisition equipment (sensors and lenses) is expensive and requires complex debugging. As the display screen is continuously updated and iterated, the hardware correction will reduce its effect. In addition, during the continuous use of the hardware, unstable factors such as bad pixels and jitter will appear on the sensor. These will greatly affect the effect of the display screen image during the software correction process, thereby reducing the effect of the flat field correction of the display screen image, and further causing the uniformity of the display screen image to decrease.

[0108] Based on this, the present application discloses a method, device, system and storage medium for flat field correction of a display screen, which are used to improve the uniformity of the image on the display screen after flat field correction.

[0109] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0110] The method of the present application can be applied to a server, a device, a terminal or other devices with logic processing capabilities, and the present application does not limit this. For the convenience of description, the following description is made by taking the execution subject as an example of a terminal.

[0111] See also Figure 1 The present application provides an embodiment of a method for flat field correction of a display screen, comprising:

[0112] 101. Collecting a plurality of frames of initial bright field images by using a collection device;

[0113] In this embodiment, the terminal first performs image acquisition on a specific display device through an existing acquisition device, and acquires several frames of initial bright field images at a specific grayscale. Assume that there are L frames of images acquired, and the size of each initial bright field image is M×N pixels. The acquisition device in this embodiment can be a variety of image acquisition devices that can perform multi-frame acquisition, specifically, different types of industrial cameras combined with corresponding shooting lenses.

[0114] 102. Perform grayscale averaging processing on a plurality of frames of initial bright field images to generate an average bright field image;

[0115] The terminal performs grayscale averaging on the initial bright field images of several frames to generate an average bright field image. Specifically, the terminal averages the L frames of initial bright field images to obtain an averaged bright field image. Specifically, the following formula can be used for averaging:

[0116] Averaged bright field image (i, j) = (image 1 (i, j) + image 2 (i, j) + ... + image L (i, j)) / L

[0117] Among them, image (i, j) represents the pixel value of the i-th row and j-th column, i is an integer from 1 to M, and j is an integer from 1 to N. With respect to each frame of the image, the pixels at the corresponding positions are superimposed and averaged to generate an average bright field image.

[0118] 103. Selecting a ROI region on the average bright field image according to the grayscale uniformity of the average bright field image;

[0119] The terminal selects the ROI region on the averaged bright field image. The size and position of the ROI region can be set according to the uniformity and actual conditions. Assume that the size of the ROI region is m×n pixels.

[0120] 104. Generate a ROI region mean value according to pixel point information of the ROI region;

[0121] The terminal calculates the average value of the ROI region and generates the ROI region mean. Specifically, the following formula can be used for calculation: ROI region mean = (ROI region (1,1) + ROI region (1,2) + ... + ROI region (m,n)) / (m × n). Among them, ROI region (i,j) represents the pixel value of the i-th row and j-th column of the ROI region.

[0122] 105. Generate a flat field correction coefficient map according to the average bright field image and the ROI area mean;

[0123] The terminal generates a corresponding flat field correction coefficient map through the ROI area mean and the average bright field image.

[0124] 106. Capture the display screen to be corrected by using a capture device, and perform flat field correction processing on the captured image to be corrected according to the flat field correction coefficient map.

[0125] The terminal collects the display screen to be corrected through the acquisition device, and performs flat field correction on the collected image to be corrected according to the flat field correction coefficient map. Specifically, each image to be corrected is multiplied by the flat field correction coefficient map to obtain the display screen image after flat field correction. Specifically, the following formula can be used for calculation:

[0126] The screen image after flattening (i, j) = the image to be corrected (i, j) × the flattening correction coefficient map (i, j)

[0127] Among them, the flattened display screen image (i, j) represents the pixel value of the i-th row and j-th column of the flattened image. It should be noted that in the above calculation process, all division and multiplication operations are performed pixel by pixel. In addition, the above steps can be implemented on a computer using relevant image processing software or programming language.

[0128] In this embodiment, first, several frames of initial bright field images are collected by an acquisition device. Then, the initial bright field images of several frames are subjected to grayscale averaging to generate an average bright field image. Multi-needle averaging can eliminate many random noises and system errors generated in the detection environment. Next, the ROI area is selected on the average bright field image according to the grayscale uniformity of the average bright field image, and the area with uniformity that meets the standard under different grayscales is determined, which is used as the reference area. The ROI area mean is generated according to the pixel information of the ROI area. Then, a flat field correction coefficient map is generated based on the average bright field image and the ROI area mean. The flat field correction coefficient map contains the flat field correction coefficient of the acquisition device on each pixel. Finally, the display screen to be corrected is collected by the acquisition device, and the pixels on the collected image to be corrected are flat-field corrected one-to-one according to the flat field correction coefficient map.

[0129] In this solution, the ROI area with uniformity that meets the standard is used as the reference area, the ROI area mean is calculated, and then the flat field correction coefficient map is generated based on the average bright field image and the ROI area mean, which can effectively reduce the problem of decreased correction effect caused by unstable factors such as bad pixels and jitter in the acquisition device sensor. Specifically, the flat field correction coefficient map is calculated using a high-precision floating point type (ROI area mean), which can obtain a more accurate flat field correction coefficient map, effectively eliminate the unevenness in the display image, and effectively improve the flat field correction effect.

[0130] See also Figure 2 The present application provides an embodiment of a method for generating an initial bright field image, comprising:

[0131] 201. Setting lighting parameters of the spherical integral light source, and lighting the spherical integral light source under the acquisition device according to the lighting parameters;

[0132] 202. The spherical integral light source is collected by a collection device to generate a plurality of frames of bright field images.

[0133] In this embodiment, the terminal sets an integral light source as a reference in advance, and lights it by setting a spherical integral light source, and then collects the spherical integral light source through a collection device to generate several frames of bright field images.

[0134] The spherical integral light source can display uniform brightness on the acquisition device as much as possible.

[0135] See also Figure 3 The present application provides an embodiment of a method for selecting a ROI region according to grayscale uniformity, comprising:

[0136] 301. Divide the average bright field image into blocks to generate a bright field central area and a plurality of hierarchical block areas, where the hierarchical block areas are areas generated by hierarchical block generation from the bright field central area layer by layer outward;

[0137] The terminal first divides the average bright field image into a central block area (bright field central area) and multiple areas surrounding the central block area. In this embodiment, the bright field central area is the central part of the spherical integral light source, which is a rectangle, and the first level block area is a hollow rectangular area surrounding the bright field central area, and the second level is a hollow rectangular area surrounding the first level block area. The current block mode can better distinguish uniformity and can be centered on the spherical integral light source.

[0138] 302. Determine a bad point coordinate set in the bright field center area and the hierarchical block area;

[0139] The terminal locates the bad pixels on the camera sensor. The positioning may be detected in advance. The bad pixels on the camera sensor can be detected in advance through multiple frames of initial flat field images.

[0140] 303. Repairing the bad points in the bad point coordinate set by using a plurality of frames of initial bright field images;

[0141] The terminal repairs the bad pixels in the bad pixel coordinate set through several frames of initial bright field images, so that the subsequent uniformity division can be performed more accurately.

[0142] 304. Perform uniformity level analysis according to the grayscale values ​​of the pixels in the bright field center area and the hierarchical block area;

[0143] The terminal performs uniformity level analysis based on the grayscale values ​​of the pixels in the bright field center area and the hierarchical block area. Specifically, it is generated by comparing the grayscale values ​​of the bright field center area and each level of the hierarchical block area.

[0144] 305. Generate a ROI region on the average bright field image according to the uniformity level analysis result and the resolution information of the average bright field image.

[0145] Finally, the terminal generates an ROI area on the average bright field image according to the uniformity level analysis results and the resolution information of the average bright field image, that is, divides the largest area that satisfies the uniformity, and uses this area for subsequent ROI area mean calculation. At this time, the ROI area mean can be more accurate, providing a more precise parameter basis for the subsequent generation of the flat field correction coefficient map.

[0146] See also Figure 4 The present application provides an embodiment of a method for processing an average bright field image by block, comprising:

[0147] 401. Marking the central area of ​​the spherical integrating light source on the average bright field image;

[0148] First, the terminal calibrates the central area of ​​the spherical integrating light source on the average bright field image. First, the spherical integrating light source is placed under the acquisition device, and the center position of the spherical integrating light source is placed at the relatively middle position of the corresponding lens, and the central area is drawn in advance.

[0149] 402. Performing a region block processing on the average bright field image according to the central area, and calculating the grayscale mean value of each block;

[0150] After the central area is determined, the remaining part is divided according to the size of the central area to generate multiple areas, and the grayscale mean is calculated for each area.

[0151] 403. Determine a set of block regions whose grayscale mean value on the average bright field image reaches a grayscale threshold range of a spherical integrated light source;

[0152] The terminal first determines the central grayscale of the spherical integral light source, and generates a grayscale threshold range based on this central grayscale value, in order to find a block area with a similar central grayscale value, thereby generating a block area set. The block area set includes at least one area that meets the grayscale threshold, and the true center position of the integral light source needs to be determined from these areas.

[0153] 404. Performing a regional distribution analysis and a grayscale center analysis on each qualified block region in the block region set, and determining the bright field center coordinates according to the regional distribution analysis results and the grayscale center analysis results;

[0154] The terminal performs regional distribution analysis and grayscale center analysis based on each qualified block area in the block area set. The regional distribution analysis is performed first, because it is possible that some block areas have reached the grayscale threshold range, but their positions are not adjacent to other block areas that meet the conditions. At this time, it is necessary to exclude such discrete areas and only retain areas that meet the grayscale conditions and have adjacent areas that meet the grayscale conditions around them. For example: there are 5 block areas that meet the grayscale threshold range, which are adjacently connected to 4 block areas to form a rectangle, and the remaining one is not adjacent to these four, so this block area needs to be excluded first.

[0155] Next, grayscale center analysis is required. Specifically, grayscale analysis is performed on the remaining pixels in the block area that meet the grayscale threshold range to determine the position of the largest part of the pixels. The center coordinates of the bright field are determined by analyzing the centroid positions of these pixels.

[0156] 405. Generate a bright field center area with the bright field center coordinates as the center, perform hierarchical block division from the bright field center area layer by layer outward, and generate a hierarchical block area on the average bright field image.

[0157] The terminal generates a bright field center area with the bright field center coordinates as the center, and performs hierarchical blocking from the bright field center area layer by layer to the outside, and generates hierarchical blocking areas on the average bright field image. In this embodiment, the bright field center area is the central part of the spherical integral light source, which is a square area, and the first level blocking area is a hollow square area surrounding the bright field center area, and the second level is a hollow square area surrounding the first level blocking area, and the thickness of each hollow square area is equal to the side length of the bright field center area. The above-mentioned bright field center coordinate generation method and blocking method can better distinguish the uniformity, and the spherical integral light source can be used as the center. With the above-mentioned blocking method, the grayscale of the pixel points in the block area of ​​each level can be more balanced, providing a basis for the subsequent extraction of ROI areas that meet the uniformity standards.

[0158] See also Figure 5 The present application provides another embodiment of a method for repairing a bad pixel of a sensor on a bright field image, comprising:

[0159] 501. Generate an initial auxiliary repair area on the initial bright field images of several frames with the bad point coordinates as the center;

[0160] There are a certain number of bad pixels on camera sensors that have been used for a long time. In general, these bad pixels are usually completely dark or completely bright and cannot show the actual brightness.

[0161] At this time, the terminal needs to generate an initial auxiliary repair area on the initial bright field images of several frames with the bad pixel coordinates as the center, that is, with each bad pixel as the center, an area covering adjacent pixels is generated on each initial bright field image. The initial auxiliary repair area is a 5*5 pixel area, with a total of 25 pixels.

[0162] 502. Calculate the attention value of normal pixels in the initial auxiliary restoration area on each initial bright field image;

[0163] The terminal calculates the attention value of the normal pixel in the initial auxiliary repair area on each initial bright field image, that is, determines the information of the normal pixel of the bad pixel in the initial auxiliary repair area of ​​each initial flat field image.

[0164] 503. Grayscale fusion is performed according to the attention value and grayscale value of normal pixels in each initial auxiliary repair area to generate a target auxiliary repair area. The number of pixels in the target auxiliary repair area is the same as that in the initial auxiliary repair area.

[0165] The terminal performs grayscale fusion based on the attention value and grayscale value of the normal pixel points in each initial auxiliary repair area to generate a target auxiliary repair area, which is also a 5*5 area.

[0166] For example: there are 5 initial bright field images and 5 initial auxiliary repair areas. Excluding the coordinates of the central bad point, each initial auxiliary repair area has 24 points. The target auxiliary repair area also has 24 blank points at the beginning. Each blank point corresponds to 5 points with grayscale values ​​(one for each of the 5 initial auxiliary repair areas). At this time, these 5 grayscale points need to be integrated into one and filled into the corresponding points of the target auxiliary repair area. The formula is as follows:

[0167]

[0168] in, The first point of the target auxiliary repair area The fused gray value, The first point of the first initial auxiliary repair area The gray value of the image, The first point of the second initial auxiliary repair area The gray value of the image, The first point of the initial auxiliary repair area in the third picture The gray value of the image, The first point of the 4th initial auxiliary repair area The gray value of the image, The first point of the fifth initial auxiliary repair area The gray value of the image, , , , , For point Attention values ​​on the 5 initial auxiliary restoration images.

[0169] 504. Repair the bad pixels according to the grayscale values ​​of the pixels in the target auxiliary repair area, so that all the bad pixels in the bad pixel coordinate set are repaired.

[0170] After calculating the grayscale values ​​of all normal points in the target auxiliary repair area, the terminal repairs the bad points according to the grayscale values ​​of the pixels in the target auxiliary repair area, so that all the bad points in the bad point coordinate set are repaired. Specifically, the target auxiliary repair area needs to be replaced with the initial auxiliary repair image of the 5 initial bright field images, and the attention value for the target auxiliary repair area is recalculated based on the pixels of the initial bright field image. Each point on the target auxiliary repair area still gets 5 attention values, and then the average of the 5 attention values ​​is taken, so that each point on the target auxiliary repair area has only one average attention value, and then the grayscale calculation is performed. The formula is as follows:

[0171]

[0172] in Bad Pixel Grayscale value after grayscale fusion, , , to is the average attention value of the 24 points in the target auxiliary repair area (calculated by averaging 5 attention values ​​at each point), Assist in repairing the upper point of the target area The grayscale value in the target auxiliary repair area, i is 1 to 24. The bad pixels repaired in the above manner can be better integrated into the image, improving the accuracy of flat field correction.

[0173] See also Figure 6 The present application provides another embodiment of a method for uniformity level analysis, comprising:

[0174] 601. Calculate the bright field center grayscale mean of the bright field center area;

[0175] 602. Calculate the level grayscale mean value set of each level block area;

[0176] 603. Perform pixel partitioning processing on each hierarchical block area to generate partitioned pixel points, and the number of pixel points in each partitioned pixel point area is the same;

[0177] 604. Calculate the grayscale mean for each partition pixel area in each level block area to generate a partition grayscale value set;

[0178] 605. Generate a first uniformity parameter for each hierarchical block area according to the bright field center grayscale mean and the hierarchical grayscale mean set;

[0179] The terminal calculates the grayscale mean of the bright field center area, and then calculates the level grayscale mean set of each level block area. And the terminal performs pixel partitioning on each level block area, specifically dividing it into square partitions of the same size, generating partition pixels, and the number of pixels in each partition pixel area is the same. Then the grayscale mean is calculated for each partition pixel area in each level block area, and a partition grayscale value set is generated. The purpose of this is to not only analyze the grayscale of each level, but also to detect the pixels in different areas of each level to determine that the grayscale uniformity of each partition in the level is satisfied.

[0180] First, the terminal generates the first uniformity parameter of each hierarchical block area according to the bright field center grayscale mean and the hierarchical grayscale mean set. Specifically, the difference between the bright field center grayscale mean and the hierarchical grayscale mean of the first-level block area is detected first, and this grayscale difference is divided by the distance to the center point (the distance from the first-level block area to the center point of the bright field center area) as the first uniformity parameter of the first-level block area. Then, the difference between the bright field center grayscale mean and the hierarchical grayscale mean of the second-level block area is detected, and this grayscale difference is divided by the distance to the center point (the distance from the second-level block area to the center point of the bright field center area) as the first uniformity parameter of the second-level block area, and so on.

[0181] 606. Determine a subarea pixel point area whose uniformity meets the standard according to the bright field center grayscale mean and the subarea grayscale value set;

[0182] The terminal then determines the partitioned pixel area that meets the uniformity standard based on the bright field center grayscale mean and the partition grayscale value set. Specifically, the difference between the bright field center grayscale mean and the grayscale mean of each partitioned pixel area is divided by the relative distance to obtain the uniformity parameter, and the partitioned pixel area whose uniformity parameter is within the preset threshold range is determined.

[0183] 607. Generate a second uniformity parameter for each level block area according to the partitioned pixel point area that meets the uniformity standard;

[0184] The terminal generates a second uniformity parameter for each hierarchical block area based on the partitioned pixel point areas that meet the uniformity standard. Specifically, the terminal determines the compliance ratio as the second uniformity parameter based on the number of partitioned pixel point areas that meet the standard divided by the total number of partitioned pixel point areas in the hierarchical block area, and determines whether the second uniformity parameter reaches the preset compliance threshold.

[0185] 608. Determine a uniformity level of each hierarchical block area according to the first uniformity parameter and the second uniformity parameter.

[0186] The terminal determines the uniformity level of each hierarchical block area according to the first uniformity parameter and the second uniformity parameter. Specifically, the terminal determines whether the first uniformity parameter and the second uniformity parameter both meet the conditions, that is, whether the unit distance grayscale difference between each hierarchical block area and the bright field center area meets the standard, and whether the unit distance grayscale difference between the partitioned pixel point area in each hierarchical block area and the bright field center area meets the standard. If all meet the standards, the level is 1; if one does not meet the standards, the level is 0.

[0187] The terminal needs to determine the hierarchical block area with a uniformity level of 1, and finally select the hierarchical block area of ​​appropriate size and its protected area as the ROI area. The above method can extract the ROI area with uniformity that meets the conditions, thereby improving the accuracy of the subsequent flat field correction coefficient map.

[0188] See also Figure 7 The present application provides another embodiment of a method for generating a flat field correction coefficient map, comprising:

[0189] 701. Divide the pixel value of the pixel point on the average bright field image by the ROI area mean value to generate a flat field correction coefficient map.

[0190] The terminal divides the average bright field image by the mean value of the ROI area to obtain a flat field correction coefficient map. Specifically, the following formula can be used for calculation:

[0191] Flat field correction coefficient map (i, j) = average bright field image (i, j) / ROI area mean

[0192] Among them, the flat field correction coefficient map (i, j) represents the pixel value of the i-th row and j-th column of the flat field coefficient map. Here, the image grayscale needs to be converted into a floating point number with higher precision for calculation, which can effectively improve the flat field effect.

[0193] See also Figure 8 The present application provides an embodiment of a device for flat field correction of a display screen, comprising:

[0194] The acquisition unit 801 is used to acquire a plurality of frames of initial bright field images through an acquisition device;

[0195] Optionally, the acquisition unit 801 includes:

[0196] Set the lighting parameters of the spherical integral light source, and light up the spherical integral light source under the acquisition device according to the lighting parameters;

[0197] The spherical integral light source is collected by an acquisition device to generate several frames of bright field images.

[0198] The first generating unit 802 is used to perform grayscale averaging processing on the initial bright field images of several frames to generate an average bright field image;

[0199] A selection unit 803 is used to select a ROI region on the average bright field image according to the grayscale uniformity of the average bright field image;

[0200] Optionally, the selection unit 803 includes:

[0201] The block division module 8031 ​​is used to perform block processing on the average bright field image to generate a bright field central area and a plurality of hierarchical block areas, where the hierarchical block areas are areas generated by hierarchical block generation from the bright field central area layer by layer outward;

[0202] Optionally, the block module 8031 ​​includes:

[0203] Mark the central area of ​​the spherical integrated light source on the average bright field image;

[0204] The average bright field image is divided into blocks according to the central area, and the grayscale mean value of each block is calculated;

[0205] Determine a set of block regions whose grayscale mean value on the average bright field image reaches the grayscale threshold range of the spherical integrated light source;

[0206] Perform regional distribution analysis and grayscale center analysis on each qualified block area in the block area set, and determine the bright field center coordinates based on the regional distribution analysis results and the grayscale center analysis results;

[0207] A bright field center area is generated with the bright field center coordinates as the center, and hierarchical blocks are performed layer by layer from the bright field center area outward to generate hierarchical block areas on the average bright field image.

[0208] A determination module 8032 is used to determine a bad point coordinate set in the bright field center area and the hierarchical block area;

[0209] The repair module 8033 is used to repair the bad points in the bad point coordinate set by using the initial bright field images of several frames;

[0210] Optionally, repair module 8033 includes:

[0211] An initial auxiliary repair area is generated on the initial bright field images of several frames with the bad point coordinates as the center;

[0212] Calculate the attention value of normal pixels in the initial auxiliary restoration area of ​​each initial bright field image;

[0213] Grayscale fusion is performed according to the attention value and grayscale value of normal pixels in each initial auxiliary repair area to generate a target auxiliary repair area. The number of pixels in the target auxiliary repair area is the same as that in the initial auxiliary repair area.

[0214] The bad pixels are repaired according to the grayscale values ​​of the pixels in the target auxiliary repair area, so that all the bad pixels in the bad pixel coordinate set are repaired.

[0215] An analysis module 8034 is used to perform uniformity level analysis based on the grayscale values ​​of the pixels in the bright field center area and the hierarchical block area;

[0216] Optionally, the analysis module 8034 includes:

[0217] Calculate the bright field center grayscale mean of the bright field center area;

[0218] Calculate the level grayscale mean set of each level block area;

[0219] Perform pixel partitioning on each hierarchical block area to generate partitioned pixels, and the number of pixels in each partitioned pixel area is the same;

[0220] Calculate the grayscale mean for each partition pixel area in each level block area to generate a partition grayscale value set;

[0221] Generate a first uniformity parameter for each hierarchical block area according to the bright field center grayscale mean and the hierarchical grayscale mean set;

[0222] Determine the subarea pixel point area that meets the uniformity standard according to the bright field center grayscale mean and the subarea grayscale value set;

[0223] Generate a second uniformity parameter for each hierarchical block area according to the partitioned pixel point area that meets the uniformity standard;

[0224] The uniformity level of each hierarchical block area is determined according to the first uniformity parameter and the second uniformity parameter.

[0225] The generating module 8035 is used to generate a ROI area on the average bright field image according to the uniformity level analysis result and the resolution information of the average bright field image.

[0226] The second generating unit 804 is used to generate the ROI region mean value according to the pixel point information of the ROI region;

[0227] The third generating unit 805 is used to generate a flat field correction coefficient map according to the average bright field image and the ROI area mean;

[0228] Optionally, the third generating unit 805 includes:

[0229] The pixel value of the pixel on the average bright field image is divided by the mean value of the ROI area to generate a flat field correction coefficient map.

[0230] The flat field correction unit 806 is used to collect the display screen to be corrected through a collection device, and perform flat field correction processing on the collected image to be corrected according to the flat field correction coefficient map.

[0231] See also Fig. 9 The present application provides a system for display screen flat field correction, comprising:

[0232] Processor 901 , memory 902 , input-output unit 903 , and bus 904 .

[0233] The processor 901 is connected to the memory 902 , the input and output unit 903 , and the bus 904 .

[0234] The memory 902 stores a program, and the processor 901 calls the program to execute the following steps: Figure 1 , Figure 2 and Figure 3 , Figure 4 , Figure 5 , Figure 6 and Figure 7 The method in .

[0235] The present application provides a computer-readable storage medium, on which a program is stored, and when the program is executed on a computer, the program performs the following steps: Figure 1 , Figure 2 and Figure 3 , Figure 4 , Figure 5 , Figure 6 and Figure 7 The method in .

[0236] Those skilled in the art can 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.

[0237] In the several embodiments provided in the present 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 only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, 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.

[0238] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0239] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0240] 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 is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable 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 method for flat field correction of a display screen, characterized in that: include: Collecting a number of frames of initial bright field images by using an acquisition device; Collecting several frames of initial bright field images through a collection device, including: setting lighting parameters of a spherical integrating light source, and lighting the spherical integrating light source under the collection device according to the lighting parameters; collecting the spherical integrating light source through the collection device to generate several frames of initial bright field images; Performing grayscale averaging processing on the initial bright field images of the plurality of frames to generate an average bright field image; Selecting a ROI region on the average bright field image according to the grayscale uniformity of the average bright field image; Selecting an ROI area on the average bright field image according to the grayscale uniformity of the average bright field image, including: performing block processing on the average bright field image to generate a bright field central area and a plurality of hierarchical block areas, wherein the hierarchical block areas are areas generated by hierarchical block generation from the bright field central area layer by layer outward; determining a bad point coordinate set in the bright field central area and the hierarchical block areas; repairing bad points in the bad point coordinate set through the initial bright field images of the plurality of frames; performing uniformity level analysis according to the grayscale values ​​of the pixels in the bright field central area and the hierarchical block areas; and generating an ROI area on the average bright field image according to the uniformity level analysis result and the resolution information of the average bright field image; Generate a ROI area mean value according to the pixel point information of the ROI area; Generate a flat field correction coefficient map according to the average bright field image and the ROI area mean; The display screen to be corrected is collected by the collection device, and the collected image to be corrected is subjected to flat field correction processing according to the flat field correction coefficient map.

2. The method according to claim 1, characterized in that The average bright field image is processed into blocks to generate a bright field center area and a plurality of hierarchical block areas, including: Marking the central area of ​​the spherical integrating light source on the average bright field image; Dividing the average bright field image into blocks according to the central area, and calculating the grayscale mean of each block; Determine a set of block regions whose grayscale mean on the average bright field image reaches a grayscale threshold range of a spherical integrated light source; Performing regional distribution analysis and grayscale center analysis on each qualified block region in the block region set, and determining the bright field center coordinates according to the regional distribution analysis results and the grayscale center analysis results; A bright field center area is generated with the bright field center coordinates as the center, and hierarchical blocks are performed layer by layer outward from the bright field center area to generate hierarchical block areas on the average bright field image.

3. The method according to claim 2, characterized in that Repairing the bad points in the bad point coordinate set by using the initial bright field images of the plurality of frames includes: Generating an initial auxiliary repair area on the initial bright field images of the plurality of frames with the bad point coordinates as the center; Calculate the attention value of normal pixels in the initial auxiliary restoration area on each initial bright field image; Grayscale fusion is performed according to the attention value and grayscale value of normal pixels in each of the initial auxiliary repair areas to generate a target auxiliary repair area, where the number of pixels in the target auxiliary repair area is the same as that in the initial auxiliary repair area; The bad pixels are repaired according to the grayscale values ​​of the pixels in the target auxiliary repair area, so that all the bad pixels in the bad pixel coordinate set are repaired.

4. The method according to claim 3, characterized in that The uniformity level analysis is performed according to the grayscale values ​​of the pixels in the bright field center area and the hierarchical block area, including: Calculate the bright field center grayscale mean of the bright field center area; Calculate the hierarchical grayscale mean value set of each hierarchical block area; Perform pixel point partitioning processing on each of the hierarchical block areas to generate partitioned pixel point areas, wherein the number of pixels in each of the partitioned pixel point areas is the same; Calculating the grayscale mean for each partition pixel point area in each of the hierarchical block areas to generate a partition grayscale value set; Generate a first uniformity parameter for each hierarchical block area according to the bright field center grayscale mean and the hierarchical grayscale mean set; Determine a subarea pixel point area whose uniformity meets the standard according to the bright field center grayscale mean and the subarea grayscale value set; Generate a second uniformity parameter for each hierarchical block area according to the partitioned pixel point area that meets the uniformity standard; The uniformity level of each of the hierarchical block areas is determined according to the first uniformity parameter and the second uniformity parameter.

5. The method according to any one of claims 1 to 4, characterized in that Generating a flat field correction coefficient map according to the average bright field image and the ROI area mean value, including: The pixel values ​​of the pixels on the average bright field image are divided by the mean value of the ROI area to generate a flat field correction coefficient map.

6. A device for flat field correction of a display screen, characterized in that: include: An acquisition unit, used for acquiring a plurality of frames of initial bright field images through an acquisition device; The acquisition unit includes: setting lighting parameters of the spherical integrating light source, and lighting the spherical integrating light source under the acquisition device according to the lighting parameters; acquiring the spherical integrating light source through the acquisition device to generate a plurality of frames of bright field images; A first generating unit is used to perform grayscale averaging processing on the initial bright field images of the plurality of frames to generate an average bright field image; A selection unit, configured to select a ROI region on the average bright field image according to the grayscale uniformity of the average bright field image; The selection unit includes: a block division module, which is used to divide the average bright field image into blocks to generate a bright field center area and a plurality of hierarchical block areas, wherein the hierarchical block areas are areas generated by hierarchical block generation from the bright field center area layer by layer; a determination module, which is used to determine a bad point coordinate set in the bright field center area and the hierarchical block areas; a repair module, which is used to repair bad points in the bad point coordinate set through initial bright field images of a plurality of frames; an analysis module, which is used to perform uniformity level analysis based on the grayscale values ​​of pixels in the bright field center area and the hierarchical block areas; and a generation module, which is used to generate an ROI area on the average bright field image based on the uniformity level analysis result and the resolution information of the average bright field image; A second generating unit, configured to generate a ROI region mean value according to the pixel point information of the ROI region; A third generating unit, configured to generate a flat field correction coefficient map according to the average bright field image and the ROI area mean; The flat field correction unit is used to collect the display screen to be corrected through the collection device, and perform flat field correction processing on the collected image to be corrected according to the flat field correction coefficient map.

7. A system for display screen flat field correction, characterized in that: include: Processor, memory, input-output unit, and bus; The processor is connected to the memory, the input and output unit, and the bus; The memory stores a program, and the processor calls the program to execute the method according to any one of claims 1 to 5.

8. A computer-readable storage medium having a program stored thereon, wherein the program, when executed on a computer, performs the method according to any one of claims 1 to 5.

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