A fan-shaped partition-based image vignetting correction method and device and a storage medium

Abstract

The application discloses a fan-shaped partition-based image vignetting correction method and device and a storage medium, and is used for improving the quality of display screen optical detection and De-Mura compensation. A polar coordinate system is constructed according to screen body parameters of a display screen; a plurality of sampling points are arranged on each concentric circle; an auxiliary vignetting correction image is generated according to the screen body parameters of the display screen, sectors and the plurality of sampling points; a gray scale acquisition list is configured; the display screen is lighted according to the gray scale acquisition list, an industrial camera is used to shoot images, and a shooting image list is generated; brightness data of each sampling point under different gray scales is acquired; gamma values of each sampling point at each shooting gray scale are calculated according to the brightness data; gray mean values of each sampling point at each shooting gray scale are calculated; a vignetting correction model is generated according to the brightness data, the gamma values and the gray mean values of the sampling points; and the vignetting correction model is used to perform vignetting correction on the sectors.

Description

Technical Field

[0001] This application relates to the field of display screen inspection, and in particular to an image vignetting correction method, apparatus and storage medium based on sector partitioning. Background Technology

[0002] With technological innovation, new display technologies (such as MicroLED and flexible foldable screens) are constantly developing. As a core link in the display industry chain, the quality testing technology of display screens continues to receive attention, and various tests on the surface of display screens have become key factors in determining the quality of display screen products.

[0003] Among these processes, optical inspection and De-Mura compensation for the display screen remain essential steps in the panel manufacturing process. The De-Mura compensation process is based on the grayscale values ​​of each pattern image captured by a high-resolution camera. Before the algorithm processing begins, the program performs a series of image preprocessing steps to ensure that the grayscale differences between the various images more accurately reflect the brightness state and Mura pattern of the display screen itself.

[0004] However, even if the image acquisition system of the display screen is adjusted to the optimal state, it is impossible to avoid the shooting errors caused by the hardware system, objective conditions, and the characteristics of the display screen itself. For example, the vignetting characteristics of the LCD panel (display screen) itself, the non-uniformity of backlight brightness, the inconsistency of the actual imaging of each pixel of the camera, and the improvements made to the pixel layer of new displays may also cause shooting errors that traditional displays do not have. All of these will cause the image captured during the De-Mura process to differ greatly from the actual brightness of each gray level of the display screen itself. This difference will cause compensation problems such as over-compensation, under-compensation, gradation drop, and panel gamma shift in De-Mura.

[0005] Currently, many manufacturers of similar optical inspection or compensation systems correct model errors by manually adjusting the compensation amplitude and then visually verifying the compensation effect, based on specific environments or camera models. Some relatively efficient image correction algorithms use ideal models to adjust for these objective errors. However, actual image acquisition systems are not ideal models. The uniformity of backlighting and the inconsistency of camera pixel imaging mean they are not centrosymmetric models. Vignetting characteristics, due to the angular deviation between the industrial camera and the display screen, are also not ideally centrosymmetric. This makes it difficult to eliminate the photographic errors caused by the display screen's vignetting characteristics, leading to a decline in the quality of optical inspection and De-Mura compensation for the display screen. Summary of the Invention

[0006] This application discloses an image vignetting correction method, apparatus, and storage medium based on sector partitioning, which can be used to improve the quality of optical inspection and De-Mura compensation of display screens.

[0007] In a first aspect, embodiments of this application provide an image vignetting correction method based on sector partitioning, comprising: constructing a polar coordinate system according to the screen parameters of the display screen; generating several sectors and several concentric circles with the same center but different radii on the polar coordinate system; setting the pole of the polar coordinate system as the first sampling point; ensuring that the radii interval of each sector is the same size and the radius difference between adjacent concentric circles is equal; setting several sampling points on each concentric circle according to the sectors, concentric circles, and preset sampling point radii, wherein the radii of the sampling points are determined by the number of sectors and the radius difference between adjacent concentric circles; and generating an image vignetting correction method based on the screen parameters of the display screen, the sectors, and the several sampling points. Vignette correction auxiliary images; configure a grayscale acquisition list containing all grayscale images needed in the display inspection and De-Mura process; illuminate the display screen according to the grayscale acquisition list and capture images using an industrial camera to generate a list of captured images; acquire brightness data of each sampling point at different grayscale levels according to the captured image list; calculate the gamma value of each sampling point at each captured grayscale level based on the brightness data; calculate the grayscale mean of each sampling point at each captured grayscale level; generate a sector-shaped vignetting correction model based on the brightness data, gamma value, and grayscale mean of the sampling points; use the vignetting correction model to perform vignetting correction on the sector.

[0008] Optionally, the step of calculating the gamma value of each sampling point at each captured gray level based on the brightness data includes: determining the 255 gray level captured image corresponding to the 255 gray level and the g gray level captured image corresponding to the g gray level, where g is an integer greater than 0 and less than 255; determining the first brightness value and the second brightness value of the target sampling point on the 255 gray level captured image and the g gray level captured image from the brightness data; calculating the gamma value of the target sampling point at the g gray level based on the first brightness value and the second brightness value, and calculating the gamma value of each sampling point at non-255 gray levels; calculating the average value by adding several gamma values ​​of each sampling point on different gray level captured images, and generating the gamma value of each sampling point on the 255 gray level captured image.

[0009] Optionally, after the step of setting several sampling points on each concentric circle according to the sector, concentric circle and preset sampling point radian, and before the step of generating a vignetting correction auxiliary image according to the screen parameters of the display screen and the sector sampling points, the image vignetting correction method further includes: drawing a circle with each sampling point as the center and a preset brightness sampling radius, so as to draw the position of each sampling point aligned by the acquisition device during brightness acquisition.

[0010] Optionally, the display screen is a quantum dot electroluminescent display screen, and the thickness of the light conversion film of the quantum dot electroluminescent display screen is non-uniform. After the step of generating a vignetting correction model for the sector based on the brightness data, gamma value, and grayscale mean of the sampling points, and before the step of using the vignetting correction model to perform vignetting correction on the sector, the image vignetting correction method further includes: detecting the thickness distribution data and refractive index distribution data of the light conversion film of the quantum dot electroluminescent display screen; calculating the average thickness data and thickness gradient data of each sampling point based on the thickness distribution data; calculating the average refractive index data and refractive index gradient data of each sampling point based on the refractive index distribution data; generating a light conversion film adjustment coefficient based on the average thickness data, thickness gradient data, average refractive index data, and refractive index gradient data; and using the light conversion film adjustment coefficient to adjust the vignetting correction model of the sector to eliminate the interference caused by the light conversion film on the quantum dot electroluminescent display screen.

[0011] Optionally, the grayscale acquisition list also includes a bitmap for distortion correction, and the captured image list also includes a distortion-corrected image, which is an image generated by capturing the image using an industrial camera after the bitmap is input to the display screen; after the step of acquiring the brightness data of each sampling point at different grayscale levels according to the captured image list, and before the steps of calculating the gamma value of each sampling point at each captured grayscale based on the brightness data, and calculating the grayscale mean of each sampling point at each captured grayscale, the image vignetting correction method further includes:

[0012] Determine the coordinates of the raster points on the distortion-corrected image; use the raster point coordinates to perform distortion correction on other images in the image list.

[0013] Optionally, after the step of acquiring brightness data of each sampling point at different gray levels according to the captured image list, and before the step of determining the coordinates of the dot matrix points on the distortion-corrected image, the image vignetting correction method further includes: determining the captured image at gray level 0 as the background image; and using the background image to perform background subtraction processing on the captured images in the captured image list other than the distortion-corrected image.

[0014] Optionally, after the step of acquiring brightness data of each sampling point at different gray levels according to the captured image list, and before the step of determining the captured image at gray level 0 as the background image, the image vignetting correction method further includes: performing exposure normalization processing on the captured images in the captured image list.

[0015] Secondly, embodiments of this application provide an image vignetting correction device based on sector partitioning, comprising: a construction unit, configured to construct a polar coordinate system according to the screen parameters of the display screen, generate several sectors and several concentric circles with the same center but different radii on the polar coordinate system, set the pole of the polar coordinate system as the first sampling point, wherein the radii interval of each sector is the same size, and the radius difference between adjacent concentric circles is equal; a setting unit, configured to set several sampling points on each concentric circle according to the sectors, concentric circles, and preset sampling point radii, wherein the radii of the sampling points are determined by the number of sectors and the radius difference between adjacent concentric circles; and a first generation unit, configured to generate according to the screen parameters of the display screen. The system generates a vignetting correction auxiliary image from a sector and several sampling points; a configuration unit is used to configure a grayscale acquisition list, which contains all grayscale images needed in the display detection and De-Mura process; a second generation unit is used to light up the display screen according to the grayscale acquisition list and use an industrial camera to capture images, generating a list of captured images; a third generation unit is used to acquire brightness data of each sampling point at different grayscale levels according to the captured image list; a first calculation unit is used to calculate the gamma value of each sampling point at each captured grayscale level based on the brightness data; a second calculation unit is used to calculate the average grayscale value of each sampling point at each captured grayscale level.

[0016] The fourth generation unit is used to generate a vignetting correction model for the sector based on the brightness data, gamma value, and grayscale mean of the sampling points; the correction unit is used to perform vignetting correction on the sector using the vignetting correction model.

[0017] Optionally, the first calculation unit specifically includes: determining the 255 grayscale captured image corresponding to the 255 grayscale and the g grayscale captured image corresponding to the g grayscale, where g is an integer greater than 0 and less than 255; determining the first brightness value and the second brightness value of the target sampling point on the 255 grayscale captured image and the g grayscale captured image from the brightness data; calculating the gamma value of the target sampling point at the g grayscale based on the first brightness value and the second brightness value, and calculating the gamma value of each sampling point at non-255 grayscale; calculating the average value by adding several gamma values ​​of each sampling point on different grayscale captured images, and generating the gamma value of each sampling point on the 255 grayscale captured image.

[0018] Optionally, after the setting unit and before the first generation unit, the image vignetting correction device further includes: an extension unit, used to draw a circle with each sampling point as the center and a preset brightness sampling radius, so as to draw the position of each sampling point aligned with the acquisition device during brightness acquisition.

[0019] Optionally, the display screen is a quantum dot electroluminescent display screen, and the thickness of the light conversion film of the quantum dot electroluminescent display screen is non-uniform. After the fourth generation unit and before the correction unit, the image vignetting correction device further includes: a detection unit for detecting the thickness distribution data and refractive index distribution data of the light conversion film of the quantum dot electroluminescent display screen; a third calculation unit for calculating the average thickness data and thickness gradient data of each sampling point based on the thickness distribution data; a fourth calculation unit for calculating the average refractive index data and refractive index gradient data of each sampling point based on the refractive index distribution data; a fifth generation unit for generating light conversion film adjustment coefficients based on the average thickness data, thickness gradient data, average refractive index data, and refractive index gradient data; and an adjustment unit for adjusting the vignetting correction model of the sector partition using the light conversion film adjustment coefficients to eliminate the interference caused by the light conversion film on the quantum dot electroluminescent display screen.

[0020] Optionally, the grayscale acquisition list also includes a bitmap for distortion correction, and the captured image list also includes a distortion-corrected image, which is an image generated by capturing an image using an industrial camera after the bitmap is input to the display screen; after the third generation unit and before the first calculation unit, the image vignetting correction device further includes: a first determining unit, used to determine the coordinates of the bitmap points on the distortion-corrected image; and a distortion correction unit, used to perform distortion correction processing on other captured images in the captured image list using the bitmap point coordinates.

[0021] Optionally, after the third generation unit and before the first determination unit, the image vignetting correction device further includes: a second determination unit, used to determine the captured image with a grayscale of 0 as the background image; and a background subtraction unit, used to perform background subtraction processing on the captured images in the captured image list other than the distortion correction image using the background image.

[0022] Optionally, after the third generation unit and before the second determination unit, the image vignetting correction device further includes a normalization unit for performing exposure normalization processing on the captured images in the captured image list.

[0023] Thirdly, embodiments of this application provide an image vignetting correction device based on sector partitioning, comprising:

[0024] Processor, memory, input / output units, and bus;

[0025] The processor is connected to memory, input / output units, and a bus;

[0026] The memory stores a program, which the processor calls to execute, as in the first aspect and any optional image vignetting correction method of the first aspect.

[0027] Fourthly, embodiments of this application provide a computer-readable storage medium storing a program that, when executed on a computer, performs the image vignetting correction method as described in the first aspect and any optional method of the first aspect.

[0028] As can be seen from the above technical solutions, the embodiments of this application have the following advantages:

[0029] In this application, a polar coordinate system is first constructed based on the screen parameters of the display. Several sectors and several concentric circles with the same center but different radii are generated on the polar coordinate system. The pole of the polar coordinate system is set as the first sampling point. The radian range of each sector is the same size, and the radius difference between adjacent concentric circles is equal. Based on the sectors, concentric circles, and preset sampling point radians, several sampling points are set on each concentric circle. The radian of the sampling points is determined by the number of sectors and the radius difference between adjacent concentric circles. A vignetting correction auxiliary image is generated based on the screen parameters, sectors, and several sampling points. A grayscale acquisition list is configured, containing all grayscale images needed in the display inspection and De-Mura process. The display is lit according to the grayscale acquisition list, and images are captured using an industrial camera, generating a list of captured images. Brightness data of each sampling point at different grayscale levels is acquired based on the captured image list. The gamma value of each sampling point at each captured grayscale level is calculated based on the brightness data. The average grayscale value of each sampling point at each captured grayscale level is calculated. A vignetting correction model for sector partitions is generated based on the brightness data, gamma value, and grayscale mean of the sampling points. The vignetting correction model is then used to perform vignetting correction on the sectors.

[0030] First, a polar coordinate system is established with the center of the display screen as the pole. Sampling points are generated by dividing the screen into sectors and concentric circles. This sampling point distribution consists of equidistant concentric circles centered on the display screen's center, with the circumference of each circle increasing proportionally to the total number of sampling points. Furthermore, the sampling points on each concentric circle are spaced evenly along the arc. This distribution design of the sampling points in the vignetting correction auxiliary image ensures uniform coverage of all areas of the panel. Next, the display screen is illuminated using the vignetting correction auxiliary image, and images at different grayscale levels are captured. Then, a vignetting correction model is calculated for each sector based on its sampling points. By dividing the display screen into multiple sector-shaped regions with identical central angles, and calculating a sector-specific vignetting correction coefficient for each sector's sampling points, the vignetting correction model can be more accurately fitted to each sector's direction. This fully considers the vignetting differences across the various sector regions of the display screen, thereby eliminating the Gamma shift problem after De-Mura compensation caused by other ideal vignetting models and improving the quality of display screen optical inspection and De-Mura compensation. Attached Figure Description

[0031] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0032] Figure 1 This is a schematic diagram of the first embodiment of the image vignetting correction method based on sector partitioning in this application;

[0033] Figure 2 This is a schematic diagram of a first embodiment of the method for calculating the gamma value of a sampling point at various shooting gray levels in this application;

[0034] Figure 3 This is a schematic diagram of the first embodiment of the sampling point preprocessing method of this application;

[0035] Figure 4 This is a schematic diagram of the first embodiment of the method for adjusting the vertigo correction model according to this application;

[0036] Figure 5 This is a schematic diagram of the first embodiment of the method for correcting distortion of captured images according to this application;

[0037] Figure 6 This is a schematic diagram of the first embodiment of the adjustment method for background subtraction processing of captured images in this application;

[0038] Figure 7 This is a schematic diagram of a first embodiment of the method for preprocessing captured images according to this application;

[0039] Figure 8 This is a schematic diagram of the first embodiment of the image vignetting correction device based on sector partitioning of this application;

[0040] Figure 9 This is a schematic diagram of a second embodiment of the image vignetting correction device based on sector partitioning according to this application;

[0041] Figure 10 This is a schematic diagram of the sampling point distribution in this application;

[0042] Figure 11 This is a schematic diagram of an auxiliary image for vignetting correction in this application;

[0043] Figure 12 This is a schematic diagram of the sampling pattern of this application;

[0044] Figure 13 This is a schematic diagram of the dot matrix pattern in this application. Detailed Implementation

[0045] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0046] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0047] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0048] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

[0049] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0050] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of 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 "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0051] In existing technologies, even if the image acquisition system of a display screen is adjusted to the optimal state, it is impossible to avoid the shooting errors caused by the hardware system, objective conditions, and the characteristics of the display screen itself. For example, the vignetting characteristics of the LCD panel (display screen) itself, the non-uniformity of backlight brightness, the inconsistency of the actual imaging of each pixel of the camera, and the improvements made to the pixel layer of new displays may also cause shooting errors that traditional displays do not have. All of these will cause the image acquired during the De-Mura process to differ greatly from the actual brightness of each gray level of the display screen itself. This difference will cause compensation problems such as over-compensation, under-compensation, gradation drop, and panel gamma shift in De-Mura.

[0052] Currently, many manufacturers of similar optical inspection or compensation systems correct model errors by manually adjusting the compensation amplitude and then visually verifying the compensation effect, based on specific environments or camera models. Some relatively efficient image correction algorithms use ideal models to adjust for these objective errors. However, actual image acquisition systems are not ideal models. The uniformity of backlighting and the inconsistency of camera pixel imaging mean they are not centrosymmetric models. Vignetting characteristics, due to the angular deviation between the industrial camera and the display screen, are also not ideally centrosymmetric. This makes it difficult to eliminate the photographic errors caused by the display screen's vignetting characteristics, leading to a decline in the quality of optical inspection and De-Mura compensation for the display screen.

[0053] Based on this, this application discloses an image vignetting correction method, apparatus and storage medium based on sector partitioning, which can improve the quality of optical inspection and De-Mura compensation of display screens.

[0054] The technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0055] The method described in this application can be applied to servers, devices, terminals, or other devices with logical processing capabilities; therefore, this application does not limit its application. For ease of description, the following description uses a terminal as the executing entity.

[0056] Please see Figure 1 This application provides an embodiment of an image vignetting correction method based on sector partitioning, comprising:

[0057] 101. Construct a polar coordinate system based on the screen parameters of the display screen. Generate a number of sectors and a number of concentric circles with the same center but different radii on the polar coordinate system. Set the pole of the polar coordinate system as the first sampling point. The radian interval size of each sector is the same, and the radius difference between adjacent concentric circles is equal.

[0058] 102. Set a number of sampling points on each concentric circle according to the sectors, concentric circles, and the preset sampling point radian. The sampling point radian is determined by the number of sectors and the radius difference between adjacent concentric circles.

[0059] 103. Generate a vignetting correction auxiliary image according to the screen parameters of the display screen, sectors, and a number of sampling points.

[0060] In this embodiment, it is necessary to determine the screen center according to the shape of the display screen, and use this as the pole to construct a polar coordinate system. Then, divide the sectors and set the concentric circles on the polar coordinate system, and set the positions of the sampling points so that the sampling points can be evenly distributed in each sector. During the preparation of some new display screens, the pixel layer is prone to annular non-uniformity. Using this type of sector division method, the sampling points can be evenly distributed, improving the quality of subsequent optical detection and De-Mura compensation.

[0061] Specifically, assume that the resolution of the display screen is (W, H), and it is the area of the first quadrant x < W, y < H in the rectangular coordinate system. Now, establish a polar coordinate system with (W / 2, H / 2) as the pole, the positive x direction as the polar axis, and the θ value range [0, 2π). The sector division and sampling point settings are as follows. If a set of parameters (n, d, r) is given, where n, d, and r are all preset constants and n is an integer, the sector division and sampling point distribution characteristics are as follows:

[0062] The entire panel area is divided into 4n sector regions (sectors), denoted as S = {S0, S1... S 4n-1}, and the radian ranges of each sector are respectively , ... , corresponding to the numbers 0, 1, 2... 4n - 1 for these radian ranges. It can be seen that the sector radian intervals of each sector region are equal.

[0063] Next, draw concentric circles with the pole as the center and radii R = 0, d, 2d... kd (k is an integer greater than or equal to 2), where , and . The sampling point distributions of each concentric circle are as follows. Please refer to Figure 10 , Figure 10 which is a schematic diagram of the sampling point distribution of this application. n is 2, and there are 8 sector regions in the figure.

[0064] When R=0, the sampling point is the extreme point (pole) itself. At this time, each sector corresponds to the same sampling point, which is also the first sampling point.

[0065] When R>0, starting from the polar axis, each concentric circle sets the sampling point with a preset sampling point radian distance as the distance, and the sampling point arc length is... As shown below:

[0066]

[0067] As can be seen, each concentric circle corresponds to 4nk sampling points.

[0068] like Figure 10 As shown, the sampling points of each sector include both sampling points that fall entirely within the sector and sampling points on the sector boundary line (red line). That is, sampling points on the sector boundary line will participate in the vignetting calculation of adjacent sectors. Therefore, the number of sampling points m corresponding to each sector is:

[0069]

[0070] In the formula The representative sector has sampling points on each concentric circle. This represents the number of sampling points repeated on even-numbered concentric circles in each sector, where 1 represents the sampling point when k=0, and their sum. This is the total number of sampling points in the current sector that participate in the vignetting correction calculation.

[0071] Please refer to Figure 10 It is an image of sector partitions and sampling point positions generated with a resolution of [3840, 2160] and parameters (2, 250, 20). The green lines are concentric circles drawn with d=250, the red lines are the dividing lines between each sector (the first sector is directly to the right, and they are marked clockwise in sequence), the black lines are the center lines of each sector, the thickened center line of the first sector is the polar axis, and each small black circle corresponds to the position of each CA410 sampling point (the small black circles will be introduced in the following embodiment 3).

[0072] Next, the terminal generates a resolution of (W, H), marks the sector partition lines, and draws a white pattern image (a vignetting correction auxiliary image) at the location of each sampling point, as shown below. Figure 11 As shown, Figure 11 This is a schematic diagram of a vignetting correction auxiliary image. It is a pattern image of a sector partition and CA410 sampling point positions generated with a resolution of [3840, 2160] and parameters (2, 250, 20). The size of this vignetting correction auxiliary image is consistent with the size of the effective display area of ​​the display screen.

[0073] 104. Configure the grayscale acquisition list, which contains all grayscale images needed for display detection and De-Mura processes.

[0074] In this embodiment, the program configures a Pattern acquisition list G (grayscale acquisition list). The grayscale list is determined based on the customer's detection requirements and the characteristics of the algorithm itself. G={g0,g...} Point ,g 255 ,g1,g2...g m ...g 254}, and set an appropriate exposure time E={E0,E} for each pattern. point E 255 E1, E2...E m ...E 254}. Where g0 is the background image (grayscale g is 0), g Point This is a bitmap image; its function will be explained in subsequent embodiments. The remaining images are grayscale sequences arranged from largest to smallest, with the first grayscale level being g. 255 =255 (i.e., the maximum grayscale value that the display can represent), the G list should contain all grayscale images that may be used in panel detection and De-Mura process, and m represents the number of sampling points in a sector, which will be used later.

[0075] 105. Light up the display screen according to the grayscale acquisition list, and use an industrial camera to capture images and generate a list of captured images.

[0076] In this embodiment, the data acquisition process is conducted in a darkroom and consists of an industrial camera (which includes dark field correction and flat field correction functions and is activated during calibration and measurement), a telephoto industrial lens, a human-machine interface, a computer, and a display screen controller.

[0077] The entire photography hardware system, display screen (with Pgamma adjusted), and backlight were placed in a darkroom working environment, while keeping the camera gain, camera working distance, lens aperture, and lens focal length unchanged for the corresponding display model in normal LCD screen detection or De-Mura compensation working state.

[0078] At this time, the terminal control uses PG to illuminate the grayscale list G (grayscale acquisition list) and display one of the Patterns (vignette correction auxiliary images for each grayscale level) on the screen. After the display stabilizes, the industrial camera is controlled to acquire the image using the set exposure time E={E0,E... point E 255 E1, E2...E m} Capture the corresponding images for each scene, repeating this image capture and refresh process until all Patterns in G have corresponding images captured, and mark them as the captured image list W={W0,W... point W 255 ,W1,W2...W m ...W 254}

[0079] 106. Collect brightness data for each sampling point at different gray levels based on the list of captured images.

[0080] Each sampling point in the grayscale sequence {g} is acquired by the terminal in the sampling pattern. 255 ,g1,g2...g m ...g 254 The brightness data at the sampling point is collected as follows:

[0081] 1. Display the vignetting correction auxiliary image on the screen, and then use the CA410 to align with the sampling point where the brightness will be collected;

[0082] 2. Click Start, and the program will display the images of the grayscale list one by one on the screen. At the same time, it will control the CA410 to collect the brightness data of the current grayscale and the current sampling point. This is a cyclical process, that is, a brightness data is collected for each image captured.

[0083] 3. Each sampling point must repeat processes 1 and 2.

[0084] The specific steps are explained in detail below:

[0085] A. Based on the user-defined parameters (n, d, r), the program will generate N = 1 + 4n + 4n*2 + ... + 4n*k buttons. Each button corresponds one-to-one with a sampling point in the Pattern, and the correspondence order is as follows: Figure 12 As shown in the diagram (numbered first in concentric circles, then in sector numbers), each button triggers the acquisition of brightness data for the corresponding sampling point. The program automatically identifies and invalidates sampling points that do not exist in the panel area, and the corresponding brightness data is set to zero. Please refer to [link / reference]. Figure 12 , Figure 12 This is a schematic diagram of the sampling point sequence. Sampling is performed based on the starting point in the diagram, and the sampling order of all points is determined according to the distance of each sampling point from the center and the counterclockwise direction.

[0086] B. Control PG device display Figure 12 Using the sampling pattern image, align the CA410 with one of the sampling points, then click the corresponding button. The program will control the panel to sort the samples according to the grayscale sequence {g}. 255 ,g1,g2...gm ...g 254 The image is sequentially refreshed. Each time the program refreshes a grayscale image, it controls the CA410 to collect the brightness data of the corresponding grayscale level at the corresponding sampling point. This continues until brightness data for all grayscale levels at the sampling points has been collected. The brightness data is recorded in Table 1. The data in black represents the brightness data collected by the CA410. Each time, the brightness data of one sampling point is collected, corresponding to one column in the table. Let the brightness data be denoted as Lv = {Lv...} 255 Lv1, Lv2...Lv m ...Lv 254 Each element in Lv corresponds to a row of brightness data in the table, which is the brightness data of all sampling points of a grayscale.

[0087] Table 1

[0088]

[0089] 107. Calculate the gamma value of each sampling point at each shooting grayscale based on the brightness data.

[0090] 108. Calculate the average gray level of each sampling point across all shooting gray levels.

[0091] 109. Generate a vignetting correction model for sector partitions based on the brightness data, gamma value, and grayscale mean of the sampling points.

[0092] 110. Use a vignetting correction model to perform vignetting correction on the sector.

[0093] In this embodiment, the terminal uses a binary gamma surface as the correction model, and calculates separate LCD viewing angle vignetting surface correction models for different sectors at different gray levels. First, the terminal calculates the gamma value of each sampling point at each shooting gray level based on the brightness data. Then, it calculates the average gray level of each sampling point at each shooting gray level. Based on the brightness data, gamma value, and average gray level of the sampling points, a vignetting correction model for the sector is generated. Finally, the vignetting correction model can be used to perform vignetting correction on the sector.

[0094] The specific details are as follows:

[0095]

[0096] in, This is the data before vignetting correction in the S sector. These are vignetting correction data, K S and image V S They are coefficient matrices of the same size that correspond to the same sector. For the data after vignetting correction, for S={S0,S1...S... 4n-1 Different sectors in}, their corresponding KS The elements in are obtained by the following formula:

[0097]

[0098] in, , , Here, (ρ, θ) represents the gamma value of the sampling point, and (ρ, θ) represents the polar coordinate parameters. Since it is a binary gamma-order surface, the correction algorithm model is called: Binary gamma-order surface LCD viewing angle vignetting correction model based on sector partitioning.

[0099] Here, let P(ρ,θ) be the image pixel coordinates with the camera as the optical axis position (ρ0,θ0) as the origin of the polar coordinate system. The optical axis position of the camera can be obtained using Zhang Zhengyou's checkerboard camera calibration method.

[0100] In this embodiment, the grayscale sequence {g} 255 ,g1,g2...g m ...g 254 In the grayscale, each sector s = {S0, S1...S} 4n-1 The vignetting correction models for the g grayscale s sector are different, but the calculation methods are basically the same. The following will describe the vignetting correction coefficient k for the g grayscale s sector. x k y The calculation steps are as follows:

[0101] As mentioned earlier, each sector, i.e., a g-level grayscale sector s, contains m sampling points, which are denoted as P={P1,P2...P...} m}, and P1 is the sampling point corresponding to the pole, i.e., the center of the panel.

[0102] After the terminal calculates the gamma value of each sampling point based on the brightness data, it captures the image W using the g grayscale. g =(W g ∈{W 255 ,W1,W2...W m ...W 254}) or the distortion-corrected image G of the g-link g (G) g ∈G={G 255 G1, G2...G m ...G 254}), calculate the average gray value of each sampling point in sector s, that is, calculate the average gray value of all pixels in a circular area with radius r*Mr centered at the current sampling point, denoted as V={V1,V2...V m}

[0103] Let the shading coefficient of grayscale sector s be k.x k y Then for V={V1,V2...V... m The mean gray level V of all sampling points in} i After multiplying by the vignetting correction factor, the mean grayscale value after vignetting correction is:

[0104]

[0105] Since i=1 is the pole, x1=0 and y1=0. x and y are the corresponding coordinates in a rectangular coordinate system, and we can deduce... , where i is the sampling point number of sector s.

[0106] For all sampling points in sector s, after vignetting correction, the ratio of their mean grayscale value to the brightness value measured by CV410 is consistent, i.e., the following equation holds:

[0107]

[0108] After simplification, we obtain the following system of m-1 equations:

[0109]

[0110] in, Lv g-1 V is the brightness value of the first sampling point in the current grayscale sector s. i V1 is the average gray level of the current sampling point region after the distortion of the g-level grayscale image, V2 is the average gray level of the first sampling point, and Lv is the average gray level of the first sampling point. g-i It is the brightness value of the i-th point in sector s.

[0111] In the above system of equations Simplify to a constant A i Then the system of equations can be simplified to:

[0112]

[0113] Next, the terminal can calculate k using the least squares method. x k y :

[0114]

[0115]

[0116] Calculate k x k y After that, a vignetting correction model can be constructed, and finally, the vignetting correction model is used to perform vignetting correction on the sector.

[0117] In this embodiment, a polar coordinate system is first constructed based on the screen parameters of the display. Several sectors and several concentric circles with the same center but different radii are generated on the polar coordinate system. The pole of the polar coordinate system is set as the first sampling point. The radian range of each sector is the same size, and the radius difference between adjacent concentric circles is equal. Based on the sectors, concentric circles, and preset sampling point radians, several sampling points are set on each concentric circle. The radian of the sampling points is determined by the number of sectors and the radius difference between adjacent concentric circles. Sector sampling points include those located within the sector and on its boundaries. A vignetting correction auxiliary image is generated based on the screen parameters, sectors, and several sampling points. A grayscale acquisition list is configured, containing all grayscale images needed for display detection and De-Mura processes. The display is lit according to the grayscale acquisition list, and images are captured using an industrial camera, generating a list of captured images. Brightness data for each sampling point at different grayscale levels is acquired based on the captured image list. The gamma value of each sampling point at each captured grayscale level is calculated based on the brightness data. Calculate the average grayscale value of each sampling point across all shooting grayscale levels. Generate a vignetting correction model for the sector based on the brightness data, gamma value, and average grayscale value of the sampling points. Apply the vignetting correction model to the sector.

[0118] First, a polar coordinate system is established with the center of the display screen as the pole. Sampling points are generated by dividing the screen into sectors and concentric circles. This sampling point distribution consists of equidistant concentric circles centered on the display screen's center, with the circumference of each circle increasing proportionally to the total number of sampling points. Furthermore, the sampling points on each concentric circle are spaced evenly along the arc. This distribution design of the sampling points in the vignetting correction auxiliary image ensures uniform coverage of all areas of the panel. Next, the display screen is illuminated using the vignetting correction auxiliary image, and images at different grayscale levels are captured. Then, a vignetting correction model is calculated for each sector based on its sampling points. By dividing the display screen into multiple sector-shaped regions with identical central angles, and calculating a sector-specific vignetting correction coefficient for each sector's sampling points, the vignetting correction model can be more accurately fitted to each sector's direction. This fully considers the vignetting differences across the various sector regions of the display screen, thereby eliminating the Gamma shift problem after De-Mura compensation caused by other ideal vignetting models and improving the quality of display screen optical inspection and De-Mura compensation.

[0119] This embodiment presents a novel binary gamma-curved surface estimation model for LCD viewing angle non-uniformity as the display grayscale changes. Furthermore, it incorporates the Gamma differences of each grayscale, sector, and sampling point on the panel into the algorithm model, which can fully consider the vignetting differences in various regions of the panel.

[0120] Furthermore, this embodiment also provides a calibration calculation process for correcting imaging system errors caused by problems such as uneven backlight brightness, inconsistency in actual imaging of each pixel of the camera, and non-uniformity of LCD viewing angle during the photography process. This can improve the optical measurement accuracy of the LCD display Mura detection and compensation system and achieve better inspection and compensation effects.

[0121] Please see Figure 2 This application provides an embodiment of a method for calculating the gamma value of a sampling point at various shooting gray levels, comprising:

[0122] 201. Determine the 255 grayscale image corresponding to grayscale 255 and the g grayscale image corresponding to grayscale g, where g is an integer greater than 0 and less than 255.

[0123] 202. Determine the first and second brightness values ​​of the target sampling point on the 255 grayscale image and the g grayscale image from the brightness data.

[0124] 203. Calculate the gamma value of the target sampling point at gray level g based on the first brightness value and the second brightness value, and calculate the gamma value of each sampling point at gray levels other than 255.

[0125] 204. Calculate the mean value by adding up several gamma values ​​of each sampling point in images captured at different gray levels, and generate the gamma value of each sampling point in an image captured at 255 gray levels.

[0126] In this embodiment, the terminal determines the 255 grayscale image corresponding to grayscale 255 and the g grayscale image corresponding to grayscale g. Then, it determines the first and second brightness values ​​of the target sampling point on the 255 grayscale and g grayscale images from the brightness data. Next, it calculates the gamma value of the target sampling point at grayscale g based on the first and second brightness values, and calculates the gamma values ​​of each sampling point at non-255 grayscale levels. Finally, it calculates the average of several gamma values ​​for each sampling point on different grayscale images, generating the gamma value of each sampling point on the 255 grayscale image. Specifically, the general formula for panel display brightness is as follows:

[0127]

[0128] The formula for calculating gamma at each sampling point in sector s can be derived as follows:

[0129]

[0130] Where g is the current grayscale value, g max It is 255, Lv(g) is the brightness value of the current sampling point in the current grayscale acquired by CA410, Lv(g)max Therefore, we can calculate the set of γ for each sampling point in sector s of grayscale g, Y=={γ1,γ2...γ... m According to the formula, γ cannot be directly calculated for grayscale 255. Therefore, in this embodiment, the γ value of each sampling point of grayscale 255 is replaced by the mean γ value of all other grayscale values ​​of the current sampling point.

[0131] Please see Figure 3 This application provides an embodiment of a sampling point preprocessing method, comprising:

[0132] 301. Draw a circle with each sampling point as the center and a preset brightness sampling radius to show the position of the acquisition device when acquiring brightness at each sampling point.

[0133] In this embodiment, the terminal draws a circle with each sampling point as the center and a brightness sampling radius r. Each sampling point generates an area for device sampling, which is the sampling position of the CA410. Please refer to... Figure 10 , Figure 10 This is a schematic diagram of the sampling point distribution screen. Each small black circle in the diagram corresponds to the location of each CA410 sampling point. The size of the sampling point distribution screen is the same as the size of the effective display area of ​​the display screen.

[0134] Please see Figure 4 This application provides an embodiment of a method for adjusting a vignetting correction model, wherein the display screen is a quantum dot electroluminescent display screen, and the light conversion film of the quantum dot electroluminescent display screen has uneven thickness, including:

[0135] 401. Detect the thickness distribution and refractive index distribution data of the light conversion film of the quantum dot electroluminescent display screen.

[0136] Quantum dot electroluminescent displays (QLEDs) are a new type of display that utilizes the electroluminescent properties of quantum dots (semiconductor nanocrystals with a size of 2-10 nanometers). Their working principle involves four key steps:

[0137] 1. Carrier injection: Under the action of an external electric field, electrons are injected from the cathode and holes are injected from the anode.

[0138] 2. Carrier migration: Electrons and holes migrate to the quantum dot emission layer through the electron transport layer and hole transport layer, respectively.

[0139] 3. Exciton formation and recombination: Electrons and holes combine within the quantum dot to form excitons (excited electron-hole pairs), and energy is released during exciton recombination.

[0140] 4. Photon emission: Energy is emitted in the form of photons, thus achieving light emission.

[0141] This process is similar to that of OLED, but quantum dots are inorganic materials, which gives QLEDs a longer lifespan and higher stability.

[0142] QLED displays offer superior color performance and a wider color gamut compared to conventional displays. Quantum dots emit light at a single wavelength, resulting in high color purity and coverage of 100% of the DCI-P3 color gamut, even approaching the BT.2020 standard, far surpassing traditional LCDs and OLEDs. Furthermore, QLED colors are adjustable; by adjusting the quantum dot size (e.g., 2nm for blue light, 4nm for green light, 6nm for red light), the emitted color can be precisely controlled, achieving full-color display. It boasts leading energy efficiency and brightness. High luminous efficiency, with quantum dot electroluminescence efficiency exceeding 90%, results in lower driving voltage for the same brightness, consuming 30%-50% less energy than OLED and 60%-70% less energy than LCD. High brightness, requiring no filters, emits light directly, with peak brightness exceeding 2000 nits, suitable for HDR content display. Excellent lifespan and stability are achieved through the advantages of inorganic materials; quantum dots are inorganic semiconductors with strong chemical and thermal stability, boasting a lifespan exceeding 100,000 hours, far surpassing OLED's 10,000-30,000 hours. It is also resistant to environmental interference, high temperatures, and humidity, making it suitable for flexible displays and wearable devices.

[0143] However, in the fabrication process of QLEDs, a quantum dot electric layer is used to replace the light-emitting layer of a traditional display. This requires the construction of the quantum dot electric layer. Current technology typically uses inkjet printing to prepare the quantum dot electric layer of QLEDs. First, quantum dot particles are synthesized in a raw solvent. Then, the synthesized quantum dot particles are separated from the raw solvent to form "ink" for inkjet printing. Then, film formation is achieved through inkjet printing. However, in this fabrication stage, after inkjet printing, the red, green, and blue quantum dot inks are precisely sprayed into their respective pixel pits, forming a liquid layer. Because some solvent remains, annealing and heating are required to evaporate the solvent and generate a uniform and smooth quantum dot film (a novel light conversion film). However, during current annealing heating processes, uneven heating leads to inconsistent solvent evaporation rates during drying, with faster evaporation at the edges than at the center. This causes the bright particles at the edges to shift towards the edge of the display due to surface tension, resulting in edge aggregation and the formation of an uneven film in the QLED, which is thinner in the center and thicker around the edges. This unevenness is ring-shaped, spreading outwards from the center point of the QLED, making it difficult to eliminate the vignetting characteristic of QLEDs. Although existing technologies can mitigate the ring-shaped film of QLEDs in various ways, they usually cannot completely eliminate it. In this embodiment, sectors are divided based on the center point, and concentric circles are generated based on the size of the display and the unevenness of the ring-shaped light conversion film. Sampling points are set on the concentric circles, allowing for individual evaluation of the unevenness characteristics of the light conversion film in different sectors. Furthermore, the sector vignetting correction coefficient can be adjusted based on the thickness and refractive index distribution of the light conversion film in each sector, which is more conducive to reducing QLED imaging errors.

[0144] 402. Calculate the mean thickness data and thickness gradient data for each sampling point based on the thickness distribution data.

[0145] 403. Calculate the mean refractive index and refractive index gradient data for each sampling point based on the refractive index distribution data.

[0146] In this embodiment, the terminal first detects the thickness distribution data and refractive index distribution data of the light conversion film of the quantum dot electroluminescent display screen. Then, it determines the thickness and refractive index of the location corresponding to each sampling point from the thickness distribution data and refractive index distribution data of the light conversion film. Then, it calculates the mean refractive index data and refractive index gradient data of each sampling point based on the refractive index distribution data.

[0147] 404. Generate the light conversion film adjustment coefficient based on the average thickness data, thickness gradient data, average refractive index data, and refractive index gradient data.

[0148] The terminal generates the light conversion film adjustment coefficient based on the average thickness data, thickness gradient data, average refractive index data, and refractive index gradient data, using the following formula:

[0149]

[0150]

[0151] in, For QLED regarding k x The adjustment coefficient of the light conversion film, and For QLED regarding k y The adjustment coefficient of the light conversion film, This is the reference thickness for the light conversion film of the current QLED model. This is the reference refractive index for the current QLED model. This represents the average thickness of the sampling point region at the sampling point coordinates (x, y) (thickness mean data). This represents the mean refractive index (mean refractive index data) of the sampling point region at the sampling point coordinates (x, y). This represents the thickness gradient data of the sampling point at coordinates (x, y) in the horizontal direction. This represents the thickness gradient data of the sampling point in the vertical direction at the sampling point coordinates (x, y). This represents the refractive index gradient data of the sampling point at coordinates (x, y) in the horizontal direction. This represents the refractive index gradient data of the sampling point in the vertical direction at the sampling point coordinates (x, y). Adjust the weight for thickness. Adjusting the weights for refractive index and The effect of thickness and refractive index on vignetting correction can be calculated using historical QLED test data. This is the thickness gradient attenuation coefficient (which can be calculated based on thickness distribution data). This is the refractive index gradient attenuation coefficient (which can be calculated based on refractive index distribution data). The formula calculates... and Capable of adjusting the vignetting coefficient k for different sectors x k y Individual adjustments were made to reduce the deviation of the vignetting correction coefficient caused by the non-uniform annular film of the QLED light conversion film, thereby improving the correction effect of the subsequent vignetting correction model.

[0152] 405. The vignetting correction model of the sector partition is adjusted using the light conversion film adjustment coefficient to eliminate the interference caused by the light conversion film on the quantum dot electroluminescent display.

[0153] In this embodiment, the terminal uses the light conversion film adjustment coefficient to adjust the vignetting correction model of the sector partition in order to eliminate the interference caused by the light conversion film on the quantum dot electroluminescent display screen. The specific formula is as follows:

[0154]

[0155]

[0156] in, and The vignetting correction coefficient is the value adjusted for sector s. and The vignetting correction coefficient before sector S adjustment. and These are the offset weights of sector s in the horizontal and vertical directions in the Cartesian coordinate system, respectively, calculated as follows:

[0157]

[0158]

[0159] The calculation method involves taking the absolute values ​​of the x and y coordinates of all sampling points in sector s (sampling points located inside the display screen) and then calculating the bias weight for each sector. Since QLEDs use annular non-uniform light conversion films, this embodiment uses thickness, refractive index, and their gradients in different directions to generate adjustment coefficients for the light conversion film that can adapt to different sectors. This allows the adjusted vignetting correction coefficients to reduce the vignetting characteristics of QLEDs, reduce photographic errors, and improve the quality of QLED optical detection and De-Mura compensation.

[0160] Please see Figure 5 This application provides an embodiment of a method for distortion correction processing of captured images. The grayscale acquisition list also includes a bitmap for distortion correction, and the captured image list also includes a distortion-corrected image. The distortion-corrected image is an image generated by capturing an image using an industrial camera after the bitmap is input to the display screen, including:

[0161] 501. Determine the coordinates of the points on the distortion-corrected image.

[0162] 502. Use the dot matrix coordinates to perform distortion correction on other captured images in the captured image list.

[0163] The terminal determines the coordinates of the raster points on the distortion-corrected image, then uses these coordinates to perform distortion correction on other images in the image list, and then uses W... point The image in W is subjected to distortion correction to obtain a new image sequence G={G 255G1, G2...G m ...G 254 In list G, each image data center corresponds to the center of the panel and also to the extreme points in the pattern sampled image. The ratio of the effective area of ​​the image in G to the panel resolution is Mr. Please refer to [reference needed]. Figure 13 , Figure 13 This is a schematic diagram of the dot matrix pattern in this application.

[0164] Please see Figure 6 This application provides an embodiment of an adjustment method for background subtraction processing of captured images, comprising:

[0165] 601. The captured image with a grayscale of 0 is selected as the background image.

[0166] 602. Use the background image to perform background subtraction processing on the captured images in the image list, excluding the distortion-corrected images.

[0167] In this embodiment, the terminal determines the captured image with a grayscale level of 0 as the background image, and uses the background image to perform background subtraction processing on the captured images in the image list, excluding the distortion-corrected images. The terminal uses the W0 image to perform background subtraction processing on the images in W respectively.

[0168] Please see Figure 7 This application provides an embodiment of a method for preprocessing captured images, comprising:

[0169] 701. Perform exposure normalization processing on the captured images in the image capture list.

[0170] Using the image list W={W0,W point W 255 ,W1,W2...W m ...W 254}, Brightness data Lv={Lv 255 Lv1, Lv2...Lv m ...Lv 254 Before calculating the vignette correction coefficient, the program will first divide W... point Exposure normalization is performed on images other than the background (i.e., each grayscale image is multiplied by 100.0 / E, and exposure normalization is only for background subtraction and has no other special meaning).

[0171] Please see Figure 8 This application provides an embodiment of an image vignetting correction device based on sector partitioning, comprising:

[0172] The construction unit 801 is used to construct a polar coordinate system based on the screen parameters of the display screen. Several sectors and several concentric circles with the same center but different radii are generated on the polar coordinate system. The pole of the polar coordinate system is set as the first sampling point. The radii range of each sector is the same and the radius difference between adjacent concentric circles is equal.

[0173] Setting unit 802 is used to set several sampling points on each concentric circle according to the sector, concentric circle and preset sampling point radii. The sampling point radii are determined by the number of sectors and the radius difference between adjacent concentric circles.

[0174] The extension unit 803 is used to draw a circle with each sampling point as the center and a preset brightness sampling radius, so as to draw the position of each sampling point aligned with the acquisition device during brightness acquisition.

[0175] The first generation unit 804 is used to generate a vignetting correction auxiliary image based on the screen parameters, sectors and several sampling points of the display screen.

[0176] Configuration unit 805 is used to configure the grayscale acquisition list, which contains all grayscale images required for display detection and De-Mura processes.

[0177] The second generation unit 806 is used to light up the display screen according to the grayscale acquisition list, and to take images using an industrial camera to generate a list of captured images. The grayscale acquisition list also includes a dot matrix image for distortion correction, and the captured image list also includes a distortion correction image. The distortion correction image is an image generated by taking images using an industrial camera after the dot matrix image is input into the display screen.

[0178] The third generation unit 807 is used to collect brightness data of each sampling point at different gray levels according to the list of captured images.

[0179] The normalization unit 808 is used to perform exposure normalization processing on the captured images in the captured image list.

[0180] The second determining unit 809 is used to determine the captured image with a grayscale of 0 as the background image.

[0181] Background subtraction unit 810 is used to perform background subtraction processing on captured images (excluding distortion-corrected images) in the captured image list using background images.

[0182] The first determining unit 811 is used to determine the coordinates of the dot matrix points on the distortion-corrected image.

[0183] The distortion correction unit 812 is used to perform distortion correction processing on other captured images in the captured image list using the dot matrix coordinates.

[0184] The first calculation unit 813 is used to calculate the gamma value of each sampling point at each shooting grayscale based on the brightness data.

[0185] Optionally, the first computing unit 813 specifically includes:

[0186] Determine the 255 grayscale image corresponding to grayscale 255 and the g grayscale image corresponding to grayscale g, where g is an integer greater than 0 and less than 255.

[0187] The first and second brightness values ​​of the target sampling point on the 255 grayscale image and the g grayscale image are determined from the brightness data.

[0188] Calculate the gamma value of the target sampling point at gray level g based on the first brightness value and the second brightness value, and calculate the gamma value of each sampling point at gray levels other than 255.

[0189] The gamma value of each sampling point in a 255-grayscale image is generated by summing several gamma values ​​of each sampling point in images captured at different grayscale levels and calculating the mean.

[0190] The second calculation unit 814 is used to calculate the average gray level of each sampling point at each shooting gray level.

[0191] The fourth generation unit 815 is used to generate a vignetting correction model for sector partitions based on the brightness data, gamma value and grayscale mean of the sampling points.

[0192] The detection unit 816 is used to detect the thickness distribution data and refractive index distribution data of the light conversion film of the quantum dot electroluminescent display screen. The display screen is a quantum dot electroluminescent display screen, and the thickness of the light conversion film of the quantum dot electroluminescent display screen is not uniform.

[0193] The third calculation unit 817 is used to calculate the mean thickness data and thickness gradient data of each sampling point based on the thickness distribution data.

[0194] The fourth calculation unit 818 is used to calculate the mean refractive index data and refractive index gradient data of each sampling point based on the refractive index distribution data.

[0195] The fifth generation unit 819 is used to generate the light conversion film adjustment coefficient based on the average thickness data, thickness gradient data, average refractive index data, and refractive index gradient data.

[0196] The adjustment unit 820 is used to adjust the vignetting correction model of the sector using the light conversion film adjustment coefficient to eliminate interference from the light conversion film on the quantum dot electroluminescent display.

[0197] Correction unit 821 is used to perform vignetting correction on sectors using a vignetting correction model.

[0198] Please see Figure 9 This application provides an image vignetting correction device based on sector partitioning, comprising:

[0199] Processor 901, memory 902, input / output unit 903, and bus 904.

[0200] The processor 901 is connected to the memory 902, the input / output unit 903, and the bus 904.

[0201] The memory 902 stores a program, and the processor 901 calls the program to execute it, such as... Figure 1 , Figure 2 and Figure 3 , Figure 4 , Figure 5 , Figure 6 and Figure 7 Image vignetting correction methods.

[0202] This application provides a computer-readable storage medium on which a program is stored, and when the program is executed on a computer, it performs the following... Figure 1 , Figure 2 and Figure 3 , Figure 4 , Figure 5 , Figure 6 and Figure 7 Image vignetting correction methods.

[0203] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0204] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between apparatuses or units through some interfaces, and may be electrical, mechanical, or other forms.

[0205] The units described as separate components may or may not be physically separate. 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 can be selected to achieve the purpose of this embodiment according to actual needs.

[0206] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0207] If the integrated unit is implemented as 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 this application, in essence, 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. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A method for correcting vignetting of an image based on sector partitioning, the method comprising: dividing a sector of the image into a plurality of subsectors; and determining a correction factor for each of the plurality of subsectors. include: A polar coordinate system is constructed based on the screen parameters of the display screen. Several sectors and several concentric circles with the same center but different radii are generated on the polar coordinate system. The pole of the polar coordinate system is set as the first sampling point. The radii range of each sector is the same and the radius difference between adjacent concentric circles is equal. Based on the sector, the concentric circle, and the preset sampling point radii, several sampling points are set on each concentric circle, and the sampling point radii are determined by the number of sectors and the radius difference between adjacent concentric circles. A vignetting correction auxiliary image is generated based on the screen parameters of the display screen, the sector, and the plurality of sampling points; Configure a grayscale acquisition list, which contains all grayscale images required for display detection and De-Mura processes; The display screen is illuminated according to the grayscale acquisition list, and an industrial camera is used to capture images to generate a list of captured images. Based on the list of captured images, collect the brightness data of each sampling point at different gray levels; Calculate the gamma value of each sampling point at each shooting grayscale based on the brightness data; Calculate the average gray level of each sampling point across all captured gray levels; A vignetting correction model for sector partitions is generated based on the brightness data, gamma value, and grayscale mean of the sampling points. The vignetting correction model is used to perform vignetting correction on the sector.

2. The image vignetting correction method according to claim 1, characterized in that, The step of calculating the gamma value of each sampling point at each shooting grayscale based on the brightness data includes: Determine the 255 grayscale image corresponding to grayscale 255 and the g grayscale image corresponding to grayscale g, where g is an integer greater than 0 and less than 255; The first brightness value and the second brightness value of the target sampling point on the 255 grayscale image and the g grayscale image are determined from the brightness data; Calculate the gamma value of the target sampling point at the g gray level based on the first brightness value and the second brightness value, and calculate the gamma value of each sampling point at a gray level other than 255. The gamma value of each sampling point in the 255 grayscale image is generated by calculating the mean value after adding several gamma values ​​of each sampling point in different grayscale images.

3. The image vignetting correction method according to claim 1, characterized in that, After the step of setting a plurality of sampling points on each of the concentric circles according to the sector, the concentric circles, and the preset sampling point radian, and before the step of generating a vignetting correction auxiliary image according to the screen parameters of the display screen, the sector, and the plurality of sampling points, the image vignetting correction method further includes: Using each sampling point as the center, draw a circle with a preset brightness sampling radius to show the position of each sampling point when the acquisition device is aligned during brightness acquisition.

4. The image vignetting correction method according to any one of claims 1 to 3, characterized in that, The display screen is a quantum dot electroluminescent display screen, and the thickness of the light conversion film of the quantum dot electroluminescent display screen is uneven; After the step of generating a vignetting correction model for a sector based on the brightness data, gamma value, and grayscale mean of the sampling points, and before the step of performing vignetting correction on the sector using the vignetting correction model, the image vignetting correction method further includes: The thickness and refractive index distribution data of the light conversion film in a quantum dot electroluminescent display were measured. Calculate the mean thickness data and thickness gradient data for each sampling point based on the thickness distribution data; Calculate the mean refractive index and refractive index gradient data for each sampling point based on the refractive index distribution data; An adjustment coefficient for the light conversion film is generated based on the average thickness data, the thickness gradient data, the average refractive index data, and the refractive index gradient data. The vignetting correction model of the sector partition is adjusted using the light conversion film adjustment coefficient to eliminate interference from the light conversion film on the quantum dot electroluminescent display.

5. The image vignetting correction method according to any one of claims 1 to 3, characterized in that, The grayscale acquisition list also includes a bitmap for distortion correction, and the captured image list also includes a distortion-corrected image, which is an image generated by capturing images using an industrial camera after the bitmap is input into the display screen. After the step of acquiring brightness data of each sampling point at different gray levels according to the captured image list, and before the step of calculating the gamma value of each sampling point at each captured gray level based on the brightness data, the image vignetting correction method further includes: Determine the coordinates of the points on the distortion-corrected image; The distortion correction process is performed on other captured images in the captured image list using the matrix point coordinates.

6. The image vignetting correction method according to claim 5, characterized in that, After the step of acquiring brightness data of each sampling point at different gray levels according to the captured image list, and before the step of determining the coordinates of the dot matrix points on the distortion-corrected image, the image vignetting correction method further includes: The image captured at 0 grayscale is designated as the background image; The background image is used to perform background subtraction processing on the captured images in the captured image list, excluding the distortion-corrected image.

7. The image vignetting correction method according to claim 6, characterized in that, After the step of acquiring brightness data of each sampling point at different gray levels according to the captured image list, and before the step of determining the captured image at gray level 0 as the background image, the image vignetting correction method further includes: Exposure normalization processing is performed on the captured images in the captured image list.

8. An image vignetting correction device based on sector partitioning, characterized in that, include: The construction unit is used to construct a polar coordinate system based on the screen parameters of the display screen, generate several sectors and several concentric circles with the same center but different radii on the polar coordinate system, set the pole of the polar coordinate system as the first sampling point, the radii interval of each sector is the same, and the radius difference of adjacent concentric circles is equal. The setting unit is used to set a plurality of sampling points on each of the concentric circles according to the sector, the concentric circles and the preset sampling point radii, wherein the sampling point radii are determined by the number of sectors and the radius difference between adjacent concentric circles. The first generation unit is used to generate a vignetting correction auxiliary image based on the screen parameters of the display screen, the sector and the plurality of sampling points; A configuration unit is used to configure a grayscale acquisition list, which contains all grayscale images required for display detection and De-Mura processes. The second generation unit is used to light up the display screen according to the grayscale acquisition list and use an industrial camera to capture images to generate a list of captured images. The third generation unit is used to collect brightness data of each sampling point at different gray levels according to the captured image list; The first calculation unit is used to calculate the gamma value of each sampling point at each shooting grayscale based on the brightness data; The second calculation unit is used to calculate the average gray level of each sampling point at each shooting gray level; The fourth generation unit is used to generate a vignetting correction model for a sector based on the brightness data, gamma value and grayscale mean of the sampling points. A correction unit is used to perform vignetting correction on the sector using the vignetting correction model.

9. The image vignetting correction device according to claim 8, characterized in that, The first computing unit specifically includes: Determine the 255 grayscale image corresponding to grayscale 255 and the g grayscale image corresponding to grayscale g, where g is an integer greater than 0 and less than 255; The first brightness value and the second brightness value of the target sampling point on the 255 grayscale image and the g grayscale image are determined from the brightness data; Calculate the gamma value of the target sampling point at the g gray level based on the first brightness value and the second brightness value, and calculate the gamma value of each sampling point at a gray level other than 255. The gamma value of each sampling point in the 255 grayscale image is generated by calculating the mean value after adding several gamma values ​​of each sampling point in different grayscale images.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium contains a program that, when executed on a computer, performs the image vignetting correction method as described in any one of claims 1 to 7.

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