Method and device for correcting display screen image visual angle unevenness and storage medium

Abstract

The invention discloses a display screen image visual angle unevenness correction method and device and a storage medium, which are used for improving the optical measurement precision of a display screen Mura inspection and compensation system. Aligning the central position of the sampling camera to the central position of the calibration screen; inputting the visual angle non-uniform calibration picture with the gray scale of g into a calibration screen; detecting an ROI (Region of Interest) on the calibration screen to generate a brightness array; inputting the pure-color picture with the gray scale of g into the calibration screen, and acquiring the pure-color picture through the sampling camera to generate a pure-color display screen image; calculating a gray average value of the pure color display screen image in the ROI region, and generating a gray average value array; performing centering normalization processing on the brightness array and the gray average array to generate normalized data; calculating a correction coefficient set according to the normalized brightness mean value data and the normalized gray mean value data; generating a group of distance arrays; and according to the distance array and the correction coefficient set, constructing a visual angle non-uniform model of the calibration screen under the gray scale g.

Description

Technical Field

[0001] Embodiments of the present application relate to the field of display screen detection, and in particular, to a method, device, and storage medium for correcting uneven viewing angle of an image on a display screen. Background Art

[0002] With the update and iteration of electronic products, the use of display screens has become more and more frequent, 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.

[0003] In the automatic AOI system and optical De-Mura system of the display screen, high-precision industrial cameras are used to shoot and image the lit display screen. However, the optical brightness and chromaticity of the display screen observed at different viewing angles are inherently non-uniform, and the Mura quality inspection standard of the display screen itself gives almost all optical parameters at a 0° field of view, which brings a large systematic error to the optical Mura inspection and Mura compensation of the display screen, resulting in a significant reduction in the inspection effect or repair effect. At the same time, the quantitative analysis of this non-uniformity related to the viewing angle is inconsistent at different display grayscale levels. Generally, lower grayscales have more serious viewing angle non-uniformity than higher grayscales; the viewing angle non-uniformity phenomenon of displays with different pixel arrangements or manufacturing processes is also different. It can be concluded that as the precision and functionality of the display screen increase, the more precise the display screen, the more complex the viewing angle non-uniformity of the display screen, and the greater the difficulty of detecting the viewing angle non-uniformity of the display screen, which in turn increases the difficulty of correcting the viewing angle non-uniformity of the display screen, reducing the correction effect of the viewing angle non-uniformity of the display screen.

[0004] At present, manufacturers of optical inspection and compensation systems for specific display screens all provide correction models by manually trying correction coefficients of different intensities under specific shooting conditions, and confirming the compensation or inspection effects through human eye observation. This method has many defects: first, the manual trial method is time-consuming and labor-intensive, and it is difficult to obtain the theoretically ideal correction effect. Secondly, the method of confirming the effect through human eye observation is too dependent on human subjective judgment, and the subjective error introduced into the system is large. Optical Mura inspection and Mura compensation of display screens sometimes require modeling of luminous characteristics under different grayscales first, and then detection or compensation. The errors introduced by manual trial and manual confirmation methods will be further transmitted to the back-end optical modeling process, resulting in the model being greatly affected by the factor of viewing angle non-uniformity, and the inspection and compensation effects are ultimately poor, which reduces the correction effect of viewing angle non-uniformity of the display screen, and thus reduces the optical measurement accuracy of the display screen Mura inspection and compensation system. Summary of the invention

[0005] The present application discloses a method, a device and a storage medium for correcting uneven viewing angle of a display screen image, which are used to improve the correction effect of uneven viewing angle of a display screen.

[0006] The first aspect of the present application discloses a method for correcting uneven viewing angle of an image on a display screen, comprising: Align the center position of the sampling camera with the center position of the calibration screen. The calibration screen and the display screen to be calibrated are of the same type. Input a viewing angle unevenness calibration picture with a gray scale of g into the calibration screen, and a number of ROI areas are distributed on the viewing angle unevenness calibration picture, and the ROI area is determined by the colorimeter for testing; Use a colorimeter to detect the ROI area on the calibration screen and generate a brightness array; Input a pure color picture with gray scale g into the calibration screen, collect it through the sampling camera, and generate a pure color display screen image; Calculate the grayscale mean of the pure color display screen image in the ROI area and generate a grayscale mean array; Performing center normalization processing on the brightness array and the grayscale mean array to generate normalized data, the normalized data including normalized brightness mean data and normalized grayscale mean data; Calculating a correction coefficient set according to the normalized brightness mean data and the normalized grayscale mean data; Generate a set of distance arrays based on the relationship between the position of each ROI area and the center position; The viewing angle unevenness model of the calibration screen at gray scale g is constructed according to the distance array and the correction coefficient set.

[0007] Optionally, the calibration screen is a flexible transparent touch screen, and the colorimeter includes a convex colorimeter and a concave colorimeter; Use a colorimeter to detect the ROI area on the calibration screen and generate a brightness array, including: The bendable transparent touch screen is bent to a preset curvature so that the front side of the transparent touch screen is located at the inner curved part; Using a convex colorimeter to detect the brightness of the ROI area on the front side of the transparent touch screen to generate a first initial brightness array; Using a concave colorimeter to detect the brightness of the ROI area on the back of the transparent touch screen to generate a second initial brightness array; A final brightness array is generated according to the first initial brightness array, the second initial brightness array and the light transmission parameter of the transparent touch screen.

[0008] Optionally, the pure color display screen image includes a front-side captured image and a back-side captured image; Calculate the grayscale mean of the pure color display screen image in the ROI area and generate a grayscale mean array, including: Performing flattening correction processing on the pixel points on the front collected image and the back collected image in the pure color display screen image; Calculate the grayscale mean of the flattened frontal captured image in the ROI area to generate a first grayscale mean array; Calculate the grayscale mean of the flattened back-side captured image in the ROI area to generate a second grayscale mean array; The final grayscale mean array is calculated according to the first grayscale mean array and the second grayscale mean array in combination with the light transmittance weight of the transparent touch screen.

[0009] Optionally, a pure color picture with grayscale g is input to the calibration screen, and is collected by a sampling camera to generate a pure color display screen image, including: A pure color image with a grayscale of g is input into the transparent touch screen, and the transparent touch screen is bent with a preset curvature; Perform back shading treatment on the transparent touch screen; Use a capture camera to shoot the transparent touch screen to generate a front capture image; Performing front shading treatment on the transparent touch screen; The transparent touch screen is photographed using a capture camera to generate a back capture image, and the front capture image and the front capture image are determined as a pure color display screen image.

[0010] Optionally, after constructing a viewing angle unevenness model of the calibration screen at gray scale g according to the distance array and the correction coefficient set, the method further includes: Generate a correction coefficient map based on the spatial position relationship of each pixel and the perspective unevenness model; Acquire the image to be corrected, and use the correction coefficient map to correct the image to be corrected to generate a corrected image; Calculate the grayscale mean corresponding to each ROI area in the corrected image and perform center normalization to obtain the corrected center normalized grayscale mean; The viewing angle non-uniformity model is evaluated based on the relative brightness of the image to be corrected, the centered normalized grayscale mean and the reference brightness.

[0011] Optionally, aligning the center position of the sampling camera with the center position of the calibration screen includes: Input the centering calibration pattern image into the calibration screen; Adjust the sampling camera so that the center of the image formed by the sampling camera is aligned with the center of the crosshairs on the calibration screen.

[0012] The second aspect of the present application discloses a device for correcting uneven viewing angle of an image on a display screen, comprising: An alignment unit, used to align the center position of the sampling camera with the center position of the calibration screen, where the calibration screen and the display screen to be calibrated are of the same type; An input unit is used to input a viewing angle unevenness calibration picture with a gray scale of g into a calibration screen, where a plurality of ROI areas are distributed on the viewing angle unevenness calibration picture, and the ROI area is determined by a colorimeter for performing detection; A first generating unit is used to detect the ROI area on the calibration screen using a colorimeter to generate a brightness array; The second generating unit is used to input a pure color picture with a gray scale of g into the calibration screen, collect it through a sampling camera, and generate a pure color display screen image; The third generating unit is used to calculate the grayscale mean of the pure color display screen image in the ROI area and generate a grayscale mean array; A fourth generating unit is used to perform centering normalization processing on the brightness array and the grayscale mean array to generate normalized data, wherein the normalized data includes normalized brightness mean data and normalized grayscale mean data; A calculation unit, used for calculating a correction coefficient set according to the normalized brightness mean data and the normalized grayscale mean data; A fifth generating unit, used for generating a set of distance arrays according to the relationship between the position of each ROI area and the center position; The construction unit is used to construct a viewing angle unevenness model of the calibration screen under gray scale g according to the distance array and the correction coefficient set.

[0013] Optionally, the calibration screen is a flexible transparent touch screen, and the colorimeter includes a convex colorimeter and a concave colorimeter; The first generation unit comprises: The bendable transparent touch screen is bent to a preset curvature so that the front side of the transparent touch screen is located at the inner curved part; Using a convex colorimeter to detect the brightness of the ROI area on the front side of the transparent touch screen to generate a first initial brightness array; Using a concave colorimeter to detect the brightness of the ROI area on the back of the transparent touch screen to generate a second initial brightness array; A final brightness array is generated according to the first initial brightness array, the second initial brightness array and the light transmission parameter of the transparent touch screen.

[0014] Optionally, the pure color display screen image includes a front-side captured image and a back-side captured image; The third generation unit includes: Performing flattening correction processing on the pixel points on the front collected image and the back collected image in the pure color display screen image; Calculate the grayscale mean of the flattened frontal captured image in the ROI area to generate a first grayscale mean array; Calculate the grayscale mean of the flattened back-side captured image in the ROI area to generate a second grayscale mean array; The final grayscale mean array is calculated according to the first grayscale mean array and the second grayscale mean array in combination with the light transmittance weight of the transparent touch screen.

[0015] Optionally, the second generation unit includes: A pure color image with a grayscale of g is input into the transparent touch screen, and the transparent touch screen is bent with a preset curvature; Perform back shading treatment on the transparent touch screen; Use a capture camera to shoot the transparent touch screen to generate a front capture image; Performing front shading treatment on the transparent touch screen; The transparent touch screen is photographed using a capture camera to generate a back capture image, and the front capture image and the front capture image are determined as a pure color display screen image.

[0016] Optionally, after constructing the unit, the device further comprises: A sixth generating unit, configured to generate a correction coefficient map according to the spatial position relationship of each pixel point and the viewing angle unevenness model; A seventh generating unit, used for acquiring an image to be corrected, correcting the image to be corrected using a correction coefficient map, and generating a corrected image; An eighth generating unit, used for calculating the grayscale mean corresponding to each ROI region in the corrected image and performing center normalization to obtain a corrected center normalized grayscale mean; The evaluation unit is used to evaluate the viewing angle non-uniformity model according to the relative brightness of the image to be corrected, the centered normalized grayscale mean and the reference brightness.

[0017] Optional, alignment unit, including: Input the centering calibration pattern image into the calibration screen; Adjust the sampling camera so that the center of the image formed by the sampling camera is aligned with the center of the crosshairs on the calibration screen.

[0018] A third aspect of the present application provides a system for correcting uneven viewing angle of an image on a display screen, comprising: 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 first aspect and any optional method of the first aspect.

[0019] 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.

[0020] It can be seen from the above technical solutions that the embodiments of the present application have the following advantages: In the present application, the center position of the sampling camera is first aligned with the center position of the calibration screen, and the center position is used as the reference position, wherein the calibration screen and the display screen to be calibrated are of the same type. The visual angle uneven calibration picture with a grayscale of g is input into the calibration screen, and a number of ROI areas are distributed on the visual angle uneven calibration picture, and the distance between each ROI area and the center position is not exactly the same, and the orientation of the ROI area is also different, wherein the ROI area is determined by the colorimeter for detection. Next, the ROI area on the calibration screen is detected using a colorimeter to generate a corresponding brightness array. Then a pure color picture with a grayscale of g is input into the calibration screen, and the sampling camera is used for acquisition to generate a pure color display screen image. The grayscale mean of the pure color display screen image in the ROI area is calculated to generate a grayscale mean array, that is, a corresponding array of grayscale mean and brightness value is generated. The brightness array and the grayscale mean array are centered and normalized to generate normalized data, and the normalized data includes normalized brightness mean data and normalized grayscale mean data. The correction coefficient set is calculated based on the normalized brightness mean data and the normalized grayscale mean data. A set of distance arrays is generated based on the relationship between the position of each ROI area and the center position. The viewing angle unevenness model of the calibration screen under grayscale g is constructed based on the distance array and the correction coefficient set. The viewing angle unevenness model of the calibration screen can perform viewing angle unevenness correction on pixels at any position on other display screens of the same type to be corrected.

[0021] The viewing angle non-uniformity of the display screen under grayscale is accurately calibrated and measured, and the viewing angle non-uniformity under grayscale is mathematically modeled to obtain a relatively unified viewing angle non-uniformity mathematical coefficient model. This mathematical coefficient model can correct the imaging system error caused by the viewing angle non-uniformity of the display screen during the shooting process, and can improve the correction effect of the viewing angle non-uniformity of the display screen, thereby improving the optical measurement accuracy of the display screen Mura inspection and compensation system. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] 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 any creative labor.

[0023] Figure 1 A schematic diagram of an embodiment of a method for correcting uneven viewing angle of an image on a display screen of the present application; Figure 2 A schematic diagram of an embodiment of a method for generating a brightness array for the present application; Figure 3A schematic diagram of an embodiment of a method for generating a grayscale mean array for the present application; Figure 4 A schematic diagram of an embodiment of a method for generating a pure color display screen image according to the present application; Figure 5 A schematic diagram of an embodiment of a method for evaluating a viewing angle non-uniformity model of the present application; Figure 6 A schematic diagram of an embodiment of a method for aligning the center position of a sampling camera and the center position of a calibration screen according to the present application; Figure 7 A schematic diagram of an embodiment of a device for correcting uneven viewing angle of an image on a display screen of the present application; Figure 8 A schematic diagram of another embodiment of the device for correcting uneven viewing angle of an image on a display screen of the present application; Fig. 9 This is a schematic diagram of an embodiment of the present application before grayscale display screen image correction; Fig.10 This is a schematic diagram of an embodiment of the present application after 25 grayscale display screen image correction. DETAILED DESCRIPTION

[0024] 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.

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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 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.

[0030] In the prior art, manufacturers of optical inspection and compensation systems for specific display screens all provide correction models by manually trying correction coefficients of different intensities under specific shooting conditions, and confirming the compensation or inspection effects through human eye observation. This method has many defects: first, the manual trial method is time-consuming and labor-intensive, and it is difficult to obtain the theoretically ideal correction effect. Secondly, the method of confirming the effect by human eye observation is too dependent on human subjective judgment, and the subjective error introduced into the system is large. Optical Mura inspection and Mura compensation of display screens sometimes require modeling of luminous characteristics under different grayscales first, and then detection or compensation. The errors introduced by manual trials and manual confirmation methods will be further transmitted to the optical modeling process at the back end, resulting in the model being greatly affected by the viewing angle non-uniformity factor, and the inspection and compensation effects are ultimately poor, which reduces the correction effect of the viewing angle non-uniformity of the display screen, and thus reduces the optical measurement accuracy of the display screen Mura inspection and compensation system.

[0031] Based on this, the present application discloses a method, device and storage medium for correcting uneven viewing angle of an image on a display screen, which are used to improve the correction effect of uneven viewing angle of a display screen.

[0032] 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.

[0033] 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.

[0034] See also Figure 1 The present application provides an embodiment of a method for correcting uneven viewing angle of an image on a display screen, comprising: 101. Align the center position of the sampling camera with the center position of the calibration screen, where the calibration screen and the display screen to be calibrated are of the same type; In this embodiment, the display screen is mainly a flat screen, and the center of the display screen can be determined, such as a VR screen, a flat screen, and a curved screen. The shape of this type of display screen conforms to a symmetrical shape, and the center position is relatively easy to determine.

[0035] First, randomly select a calibration screen of the same type and specification as the display screen to be calibrated, and then align the center position of the sampling camera with the center position of the calibration screen.

[0036] 102. Input a viewing angle unevenness calibration picture with a gray scale of g into a calibration screen, where a plurality of ROI areas are distributed on the viewing angle unevenness calibration picture, and the ROI area is determined by a colorimeter for performing detection; The terminal switches the signal generator to point the screen so that the screen displays the viewing angle unevenness calibration Pattern screen (viewing angle unevenness calibration screen). Specifically, the viewing angle unevenness calibration screen with a grayscale of g is input into the calibration screen. There are several ROI areas distributed on the viewing angle unevenness calibration screen, and the ROI area is determined by the colorimeter implementing the detection.

[0037] 103. Use a colorimeter to detect the ROI area on the calibration screen and generate a brightness array; The terminal uses a colorimeter to detect the ROI area on the calibration screen and generate a brightness array. Specifically, a point colorimeter (such as CA-VP410 or CA-VP427) is used to measure the brightness value of the display screen in each ROI area, which is recorded as a brightness array of length m×n: L g . Usually the recording order is set from left to right, from top to bottom, and can be set flexibly.

[0038] 104. Input a pure color picture with grayscale g into the calibration screen, collect it through a sampling camera, and generate a pure color display screen image; The terminal inputs a pure color picture with a grayscale of g into the calibration screen, collects it through the sampling camera, and generates a pure color display screen image. Specifically, the terminal switches the signal generator to point the screen image so that the calibration screen displays a pure color pattern picture with a grayscale of g (without a calibration ROI frame). Adjust the exposure time of the sampling camera to take a picture of the calibration screen, and obtain a pure color pattern display screen image with a grayscale of g (pure color display screen image), which is recorded as image I g .

[0039] At this point, the data acquisition is completed, and the actual brightness array L of the display screen under grayscale g is obtained: g and solid color display image I g .

[0040] 105. Calculate the grayscale mean of the pure color display screen image in the ROI area and generate a grayscale mean array; The terminal first obtains the pure color display screen image I g The image type type, if type is not double type, the solid color display image I g Convert to double type. Calculate the grayscale mean of the pure color display image in the ROI area and generate a grayscale mean array. Calculate image I g The grayscale mean in each calibrated ROI area is used to obtain a grayscale mean array of length m×n, denoted as: G g , the order of the corresponding recorded grayscale mean values ​​is consistent with the brightness data.

[0041] 106. Performing center normalization processing on the brightness array and the grayscale mean array to generate normalized data, wherein the normalized data includes normalized brightness mean data and normalized grayscale mean data; The brightness array L g And grayscale mean array G g Perform centering normalization, that is, first obtain the data L g , G g The value L at the center of the data length gc , G gc (i.e., the brightness data and grayscale mean of the ROI area in the center of the image), and then L g Divide each value by L gc , G g Divide each value by G gc , we can get the normalized brightness and grayscale mean, which are denoted as L g_Norm , G g_Norm , expressed as:

[0042]

[0043] Where L gc , G gc Respectively represent the array L g , G g The value at the center of the data length.

[0044] 107. Calculate a correction coefficient set according to the normalized brightness mean data and the normalized grayscale mean data; The terminal calculates the ideal correction coefficient Kg corresponding to each ROI area. Specifically, the terminal calculates the correction coefficient set according to the normalized brightness mean data and the normalized grayscale mean data. The significance of the display viewing angle unevenness correction is to obtain the image I g The ideal relative brightness is restored in the ROI, and the normalized data L is obtained according to the real brightness of the known ROI area. g_Norm (can be regarded as the ideal relative brightness) and the grayscale mean G after centering and normalization g_Norm (can be regarded as the true relative brightness), so L g_Norm , G g_Norm Calculate the ideal correction coefficient K corresponding to each ROI area g , expressed as:

[0045] 108. Generate a set of distance arrays according to the relationship between the position of each ROI area and the center position; 109. Construct a viewing angle unevenness model of the calibration screen at gray scale g according to the distance array and the correction coefficient set.

[0046] The terminal uses the calibration screen to determine the spatial position of the ROI area relative to the image center and the ideal correction coefficient K g Modeling of perspective unevenness. The perspective relationship reflected in the camera image can be roughly understood as the spatial position relationship of pixels relative to the center of the image. Therefore, the spatial position of the ROI area relative to the center of the image and the ideal correction coefficient K are considered here. g Modeling of uneven viewing angle is performed. The specific modeling method is as follows: Calculate the distance from the center of each ROI area to the center of the image to obtain a set of distance data, recorded as dist. Similarly, the order of the corresponding recorded spatial distances is consistent with the aforementioned brightness data. Take the spatial distance dist as the independent variable and the ideal correction coefficient Kg as the dependent variable. Use the least squares method to perform polynomial fitting on Kg and dist to obtain the viewing angle unevenness model of the display screen under grayscale g, recorded as f(dist).

[0047] It is worth noting that the above-mentioned viewing angle unevenness modeling method is only one of the specific embodiments listed. Similarly, the horizontal direction and the vertical direction can also be separated and fitted and modeled separately, or surface fitting, machine learning and other methods can be used for modeling.

[0048] In this embodiment, the center position of the sampling camera is first aligned with the center position of the calibration screen, and the center position is used as the reference position, wherein the calibration screen and the display screen to be calibrated are of the same type. The visual angle unevenness calibration picture with a grayscale of g is input into the calibration screen, and a number of ROI areas are distributed on the visual angle unevenness calibration picture, and the distance between each ROI area and the center position is not exactly the same, and the orientation of the ROI area is also different, wherein the ROI area is determined by the colorimeter for detection. Next, the ROI area on the calibration screen is detected using a colorimeter to generate a corresponding brightness array. Then, a pure color picture with a grayscale of g is input into the calibration screen, and the sampling camera is used to collect it to generate a pure color display screen image. The grayscale mean of the pure color display screen image in the ROI area is calculated to generate a grayscale mean array, that is, a corresponding array of grayscale mean and brightness value is generated. The brightness array and the grayscale mean array are centered and normalized to generate normalized data, and the normalized data includes normalized brightness mean data and normalized grayscale mean data. The correction coefficient set is calculated based on the normalized brightness mean data and the normalized grayscale mean data. A set of distance arrays is generated based on the relationship between the position of each ROI area and the center position. The viewing angle unevenness model of the calibration screen under grayscale g is constructed based on the distance array and the correction coefficient set. The viewing angle unevenness model of the calibration screen can perform viewing angle unevenness correction on pixels at any position on other display screens of the same type to be corrected.

[0049] The viewing angle non-uniformity of the display screen under grayscale is accurately calibrated and measured, and the viewing angle non-uniformity under grayscale is mathematically modeled to obtain a relatively unified viewing angle non-uniformity mathematical coefficient model. This mathematical coefficient model can correct the imaging system error caused by the viewing angle non-uniformity of the display screen during the shooting process, and can improve the correction effect of the viewing angle non-uniformity of the display screen, thereby improving the optical measurement accuracy of the display screen Mura inspection and compensation system.

[0050] See also Figure 2 The calibration screen of the present application is a flexible transparent touch screen, the colorimeter includes a convex colorimeter and a concave colorimeter, and the present application provides an embodiment of a method for generating a brightness array, including: 201. Bend the bendable transparent touch screen to a preset curvature so that the front side of the transparent touch screen is located at the inner curved part; In this embodiment, in addition to constructing a model for a flat screen, a viewing angle non-uniformity correction model can also be constructed for a special type of display screen.

[0051] Specifically, the display screen in this embodiment is a bendable transparent touch screen. There are many differences between bendable transparent touch screen and flat screen. First, bendable transparent touch screen needs to be bent to different degrees during use. The bending degree of each pixel point is different. Therefore, in the detection process, the detection effect of brightness detection, mean value detection and other links is very different from that of flat screen. Flat screen displays to users through a plane, and after the flat screen is bent, its display effect will change. Secondly, in addition to the bending factor, the light transmittance of transparent display screen will also have a great impact on the correction of viewing angle non-uniformity, because when there are abnormalities, defects or deviations in the pixels of transparent touch screen, part of the light displayed on the front will be transmitted to the rear. Even if the pixels meet the standards, there may be slight deviations, and part of the light displayed on the front will be transmitted to the rear, causing the actual display grayscale and actual brightness to not meet the requirements of the preset input image. In the detection process, the detected grayscale brightness is also different from the preset input image.

[0052] In addition, the two characteristics of bending and transparency make it more difficult to correct the viewing angle non-uniformity of this type of flexible transparent touch screen (especially when there are abnormalities, defects or deviations in the pixels), because this type of flexible transparent touch screen usually needs to be bent to different degrees during use. At any degree of bending at any gray scale, the display of the transparent touch screen will be different, because the optical fiber displayed on the front is not transmitted to a plane at the rear, but a concave or convex surface, which makes the reflected light more complicated, and the difference between the actual grayscale mean and brightness and the input image is more complicated. If the traditional grayscale mean and brightness detection method for flat screens is applied to flexible transparent touch screens, the accuracy of the detection results will be reduced.

[0053] Secondly, this embodiment provides a calibration calculation process for correcting the imaging system error caused by the non-uniform viewing angle of the LCD display during the shooting process, which can be used to improve the optical measurement accuracy of the LCD display Mura inspection and compensation system, and further achieve better inspection and compensation effects.

[0054] Secondly, this embodiment provides a mathematical model for correcting the viewing angle non-uniformity of an LCD display screen. The model can be used to achieve optimal correction coefficients for the viewing angle non-uniformity of the display screen, thereby improving the calculation accuracy of the Mura inspection and compensation system.

[0055] Secondly, the viewing angle non-uniformity mathematical modeling method provided in this embodiment has high calculation efficiency and can quickly calculate the non-uniformity correction coefficient of a single image.

[0056] In this embodiment, a detection method specifically for the flexible transparent touch screen is used to obtain data and improve the accuracy of the viewing angle non-uniformity correction of the flexible transparent touch screen.

[0057] First, the terminal bends the bendable transparent touch screen to a preset curvature so that the front of the transparent touch screen is located at the inner curved part, that is, the bendable transparent touch screen is first adjusted to a preset bending degree.

[0058] It should be noted that the front of the transparent touch screen in this embodiment is located at the inner curved part. In other cases, the front may be located at the outer curved part, that is, the front of the display screen may be concave or convex, and the calculation method is similar.

[0059] 202. Use a convex colorimeter to detect the brightness of the ROI area on the front side of the transparent touch screen to generate a first initial brightness array; When the front of the display screen is concave, a convex colorimeter is used to detect the brightness of the ROI area on the front of the transparent touch screen to generate a first initial brightness array. At this time, the detection port of the convex colorimeter and the curved transparent touch screen are consistent with each other, which can improve the accuracy of brightness detection.

[0060] If the front side of the display screen is convex, a concave colorimeter is used to detect the brightness of the ROI area on the front side of the transparent touch screen.

[0061] 203. Use a concave colorimeter to detect the brightness of the ROI area on the back of the transparent touch screen to generate a second initial brightness array; Next, the terminal uses a concave colorimeter to detect the brightness of the ROI area on the back of the transparent touch screen to generate a second initial brightness array.

[0062] 204. Generate a final brightness array according to the first initial brightness array, the second initial brightness array and a light transmittance parameter of the transparent touch screen.

[0063] Because when the transparent touch screen displays a grayscale g image, some pixels with slight defects will cause part of the light to be unable to be fully displayed from the front, and will be displayed to the back, and the back will be reflected twice, making the grayscale displayed on the real surface more complex. The terminal needs to generate the final brightness array based on the first initial brightness array, the second initial brightness array and the light transmission parameters of the transparent touch screen.

[0064] The light transmittance parameter refers to a small reference screen (a bendable transparent touch screen with a main display inside and all the pixels installed meet the standards) at a preset bending degree. A flexible screen (opaque) is used to display a grayscale g pure color image. The screen is attached to the back of the bendable transparent touch screen and the light transmittance is detected from the front to obtain the first light transmittance parameter T. g1(The brightness of the flexible screen itself is detected and divided by the brightness detected from the front of the flexible transparent touch screen), and then it is attached to the front of the flexible transparent touch screen, and the transmittance is detected from the back to obtain the second transmittance parameter T g2 .

[0065] The terminal generates a final brightness array according to the first initial brightness array, the second initial brightness array and the light transmittance parameter of the transparent touch screen. Specifically, the first light transmittance parameter and the second light transmittance parameter are used to supplement and calculate the brightness values ​​corresponding to the first initial brightness array and the second initial brightness array. The formula is as follows: L * =T g1 *L 1i +(1-T g2 )*L 2i L * is the final brightness data, the first light transmission parameter T g1 , the second light transmission parameter T g2 , L 1i is the brightness data of the i-th ROI area in the first initial brightness array, L 2i is the brightness data of the i-th ROI area in the second initial brightness array.

[0066] In the above method, a convex colorimeter and a concave colorimeter are combined to effectively eliminate the problems caused by the combination of the two characteristics of bending and transparency of the flexible transparent touch screen by calculating the transmittance parameters. In the process of correcting the viewing angle non-uniformity, highly accurate brightness data is effectively obtained, which improves the accuracy of subsequent corrections.

[0067] See also Figure 3 In the present application, the pure color display screen image includes a front-side captured image and a back-side captured image. The present application provides an embodiment of a method for generating a grayscale mean array, including: 301. Performing flattening correction processing on pixel points on the front collected image and the back collected image in the pure color display screen image; 302. Calculate the grayscale mean of the flattened frontal captured image in the ROI area to generate a first grayscale mean array; 303. Calculate the grayscale mean of the flattened back side captured image in the ROI area to generate a second grayscale mean array; 304. Calculate a final grayscale mean array according to the first grayscale mean array and the second grayscale mean array in combination with the light transmittance weight of the transparent touch screen.

[0068] In this embodiment, due to the two characteristics of bending and transparency, the grayscale will also be affected, but this type of impact is not as large as the brightness. The terminal needs to first flatten and correct the pixels on the front and back captured images in the pure color display screen image so that the pixels of the two images can correspond one to one. Flattening correction is a method of flattening the pixel coordinates into the shape of a flat screen, and then combining the interpolation method to complete the pixels to obtain two images. The terminal calculates the grayscale mean of the flattened front captured image in the ROI area to generate a first grayscale mean array, and then calculates the grayscale mean of the flattened back captured image in the ROI area to generate a second grayscale mean array. Finally, the real grayscale mean is calculated through the light transmittance weight.

[0069] U * =Ƞ 1 *U 1i +Ƞ 2 *U 2i U * is the final grayscale mean array, U 1i is the grayscale mean data of the i-th ROI area in the first initial brightness array, U 2i is the grayscale mean data of the i-th ROI area in the second initial brightness array. 1 and 2 is the grayscale transmittance weight of the transparent touch screen on the front and back. The calculation method is to use a flexible screen (opaque) to display a grayscale g pure color picture, attach it to the back of the flexible transparent touch screen, shoot an image from the front, detect the first real-time grayscale mean, and divide the first grayscale g by the real-time grayscale mean to obtain the first parameter. Then attach it to the front of the flexible transparent touch screen, shoot an image from the back, detect the second real-time grayscale mean, and divide the first grayscale g by the real-time grayscale mean to obtain the second parameter. The first parameter and the second parameter are normalized to generate two grayscale transmittance weights that add up to 1, which are the grayscale transmittance weight of the transparent touch screen on the front, Ƞ 1 and the grayscale transmittance weight on the back side Ƞ 2 This method can effectively reduce the influence of the two characteristics of bending and transparency on the grayscale mean. By using the flexible screen in conjunction with the display of the grayscale g image, the grayscale mean of the front and back sides is calculated through weights, which effectively reduces the error. In the process of viewing angle non-uniformity correction, highly accurate grayscale mean data is effectively obtained, which improves the accuracy of subsequent corrections.

[0070] See also Figure 4 The present application provides an embodiment of a method for generating a pure color display screen image, comprising: 401. Inputting a pure color image with grayscale g into the transparent touch screen, the transparent touch screen is bent with a preset curvature; 402. Performing back shading processing on the transparent touch screen; 403. Use a capture camera to photograph the transparent touch screen to generate a front capture image; 404. Performing front shading processing on the transparent touch screen; 405. Use a capture camera to photograph the transparent touch screen to generate a back capture image, and determine the front capture image and the front capture image as a pure color display screen image.

[0071] The terminal first inputs a pure color picture with a grayscale of g into the transparent touch screen, and the transparent touch screen is bent at a preset curvature. Next, the transparent touch screen is subjected to back shading processing to reduce the situation where the light projected from the pixel points to the back is reflected again. Then the terminal uses the acquisition camera to shoot the transparent touch screen to generate a front acquisition image. The transparent touch screen is then subjected to front shading processing, and the acquisition camera is used to shoot the transparent touch screen to generate a back acquisition image, and the front acquisition image and the front acquisition image are determined as pure color display screen images. In the traditional method, only a darkroom environment is used for shooting. In this embodiment, not only a darkroom environment is adopted, but also front and back shading processing is required, which further reduces the occurrence of complex situations such as light refraction and reflection, and improves the accuracy of subsequent calculations.

[0072] See also Figure 5 The present application provides an embodiment of a method for evaluating a viewing angle non-uniformity model, comprising: 501. Generate a correction coefficient map according to the spatial position relationship of each pixel and the viewing angle unevenness model; 502. Acquire an image to be corrected, and correct the image to be corrected using a correction coefficient map to generate a corrected image; 503. Calculate the grayscale mean corresponding to each ROI region in the corrected image and perform center normalization to obtain a corrected center normalized grayscale mean; 504. Evaluate the viewing angle non-uniformity model according to the relative brightness of the image to be corrected, the centered normalized grayscale mean, and the reference brightness.

[0073] In this embodiment, the terminal first calculates a correction coefficient map. The correction coefficient map is generated according to the spatial position relationship of each pixel point and the viewing angle unevenness model. Specifically, a correction coefficient map is calculated according to the spatial position relationship of each pixel point on the image and the viewing angle unevenness model obtained by calibration modeling, and is recorded as I COE For example, according to the above embodiment: first, the distance dist_i of each pixel on the image relative to the center of the image can be calculated, and then the corresponding correction coefficient can be calculated according to the model f(dist), so that the correction coefficient diagram I can be obtained by using parallel computing and multi-core optimization. COE .

[0074] Next, the viewing angle unevenness correction is performed. The terminal obtains the image to be corrected and uses the correction coefficient map to correct the image to be corrected to generate a corrected image. g Figure I with correction factor COE Perform image multiplication to obtain the corrected image I correct .

[0075] Please refer to Fig. 9 and Fig.10 , Fig. 9 and Fig.10 The images before and after the 25 grayscale correction in one embodiment are shown. It can be seen that the image after correction is better than the image before correction, and the correction model obtained by using the calibration screen has a good correction effect.

[0076] Next, the correction effect is evaluated. The terminal calculates the grayscale mean corresponding to each ROI area in the corrected image and performs center normalization to obtain the corrected center normalized grayscale mean. Specifically, the terminal calculates the grayscale mean corresponding to each calibrated ROI area in the corrected image Icorrect and performs center normalization to obtain the corrected center normalized grayscale mean (which can be regarded as the relative brightness after correction), which is recorded as G correct_Norm The viewing angle unevenness model is evaluated according to the relative brightness of the image to be corrected, the centered normalized grayscale mean and the reference brightness. Specifically, the relative brightness G before correction is known. g_Norm , and the ideal relative brightness L g_Norm Therefore, the similarity between the relative brightness before and after correction and the ideal relative brightness can be calculated to evaluate the correction effect. The similarity measurement method can adopt the Euclidean distance method, Manhattan distance, Chebyshev distance, cosine similarity and Hamming similarity.

[0077] See also Figure 6 The present application provides an embodiment of a method for aligning a sampling camera center position and a calibration screen center position, comprising: 601. Input the centering calibration pattern picture into the calibration screen; 602. Adjust the sampling camera so that the center of the image formed by the sampling camera is aligned with the center of the crosshairs of the calibration screen.

[0078] First, the terminal randomly selects a calibration screen of the same specification and type as the display screen to be calibrated, and then aligns the center position of the sampling camera with the center position of the calibration screen. Specifically, the terminal creates a cross-centering calibration pattern image (centering calibration pattern screen) with a grayscale of g, imports the cross-centering calibration pattern image into the signal generator, lights up the calibration screen and displays the cross-centering pattern screen. Next, the terminal adjusts the camera to align the image center of the sampling camera with the center of the crosshairs of the display screen.

[0079] See also Figure 7 The present application provides an embodiment of a device for correcting uneven viewing angle of an image on a display screen, comprising: An alignment unit 701 is used to align the center position of the sampling camera with the center position of the calibration screen, where the calibration screen and the display screen to be calibrated are of the same type; Optionally, the alignment unit 701 includes: Input the centering calibration pattern image into the calibration screen; Adjust the sampling camera so that the center of the image formed by the sampling camera is aligned with the center of the crosshairs on the calibration screen.

[0080] An input unit 702 is used to input a viewing angle unevenness calibration picture with a gray scale of g into a calibration screen, where a plurality of ROI areas are distributed on the viewing angle unevenness calibration picture, and the ROI area is determined by a colorimeter for performing detection; The first generating unit 703 is used to detect the ROI area on the calibration screen using a colorimeter to generate a brightness array; Optionally, the calibration screen is a flexible transparent touch screen, and the colorimeter includes a convex colorimeter and a concave colorimeter; The first generating unit 703 includes: The bendable transparent touch screen is bent to a preset curvature so that the front side of the transparent touch screen is located at the inner curved part; Using a convex colorimeter to detect the brightness of the ROI area on the front side of the transparent touch screen to generate a first initial brightness array; Using a concave colorimeter to detect the brightness of the ROI area on the back of the transparent touch screen to generate a second initial brightness array; A final brightness array is generated according to the first initial brightness array, the second initial brightness array and the light transmission parameter of the transparent touch screen.

[0081] The second generating unit 704 is used to input a pure color picture with a gray scale of g into the calibration screen, collect it through a sampling camera, and generate a pure color display screen image; Optionally, the second generating unit 704 includes: A pure color image with a grayscale of g is input into the transparent touch screen, and the transparent touch screen is bent with a preset curvature; Perform back shading treatment on the transparent touch screen; Use a capture camera to shoot the transparent touch screen to generate a front capture image; Performing front shading treatment on the transparent touch screen; The transparent touch screen is photographed using a capture camera to generate a back capture image, and the front capture image and the front capture image are determined as a pure color display screen image.

[0082] The third generating unit 705 is used to calculate the grayscale mean of the pure color display screen image in the ROI area and generate a grayscale mean array; Optionally, the pure color display screen image includes a front-side captured image and a back-side captured image; The third generating unit 705 includes: Performing flattening correction processing on the pixel points on the front collected image and the back collected image in the pure color display screen image; Calculate the grayscale mean of the flattened frontal captured image in the ROI area to generate a first grayscale mean array; Calculate the grayscale mean of the flattened back-side captured image in the ROI area to generate a second grayscale mean array; The final grayscale mean array is calculated according to the first grayscale mean array and the second grayscale mean array in combination with the light transmittance weight of the transparent touch screen.

[0083] The fourth generating unit 706 is used to perform centering normalization processing on the brightness array and the grayscale mean array to generate normalized data, where the normalized data includes normalized brightness mean data and normalized grayscale mean data; A calculation unit 707, configured to calculate a correction coefficient set according to the normalized brightness mean data and the normalized grayscale mean data; A fifth generating unit 708, configured to generate a set of distance arrays according to the relationship between the position of each ROI region and the center position; A construction unit 709, configured to construct a viewing angle unevenness model of the calibration screen at gray scale g according to the distance array and the correction coefficient set; A sixth generating unit 710, configured to generate a correction coefficient map according to the spatial position relationship of each pixel point and the viewing angle unevenness model; A seventh generating unit 711 is used to obtain an image to be corrected, and correct the image to be corrected using a correction coefficient map to generate a corrected image; The eighth generating unit 712 is used to calculate the grayscale mean corresponding to each ROI region in the corrected image and perform center normalization to obtain a corrected center normalized grayscale mean; The evaluation unit 713 is used to evaluate the viewing angle non-uniformity model according to the relative brightness of the image to be corrected, the centered normalized grayscale mean and the reference brightness.

[0084] See also Figure 8 The present application provides a device for correcting uneven viewing angle of an image on a display screen, comprising: Processor 801 , memory 802 , input-output unit 803 , and bus 804 .

[0085] The processor 801 is connected to the memory 802 , the input and output unit 803 , and the bus 804 .

[0086] The memory 802 stores a program, and the processor 801 calls the program to execute the following steps: Figure 1 , Figure 2 and Figure 3 , Figure 4 , Figure 5 and Figure 6 The method in .

[0087] 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 and Figure 6 The method in .

[0088] 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.

[0089] 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.

[0090] 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.

[0091] 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.

[0092] 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 correcting uneven viewing angle of an image on a display screen, characterized in that: include: Align the center position of the sampling camera with the center position of the calibration screen, where the calibration screen is of the same type as the display screen to be calibrated; Inputting a viewing angle unevenness calibration picture with a gray scale of g into the calibration screen, wherein a plurality of ROI areas are distributed on the viewing angle unevenness calibration picture, and the ROI areas are determined by a colorimeter for performing detection; Using the colorimeter to detect the ROI area on the calibration screen to generate a brightness array; Inputting a pure color picture with a gray scale of g into the calibration screen, collecting it through the sampling camera, and generating a pure color display screen image; Calculate the grayscale mean of the pure color display screen image in the ROI area to generate a grayscale mean array; Performing centering normalization processing on the brightness array and the grayscale mean array to generate normalized data, wherein the normalized data includes normalized brightness mean data and normalized grayscale mean data; Calculating a correction coefficient set according to the normalized brightness mean data and the normalized grayscale mean data; Generate a set of distance arrays based on the relationship between the position of each ROI area and the center position; A viewing angle non-uniformity model of the calibration screen at gray scale g is constructed according to the distance array and the correction coefficient set.

2. The method according to claim 1, characterized in that The calibration screen is a bendable transparent touch screen, and the colorimeter includes a convex colorimeter and a concave colorimeter; Using the colorimeter to detect the ROI area on the calibration screen to generate a brightness array includes: The bendable transparent touch screen is bent with a preset curvature so that the front side of the transparent touch screen is located at the inner curved part; Using a convex colorimeter to detect the brightness of the ROI area on the front side of the transparent touch screen to generate a first initial brightness array; Using a concave colorimeter to detect the brightness of the ROI area on the back of the transparent touch screen to generate a second initial brightness array; A final brightness array is generated according to the first initial brightness array, the second initial brightness array and the light transmittance parameter of the transparent touch screen.

3. The method according to claim 2, characterized in that The pure color display screen image includes a front-side captured image and a back-side captured image; Calculating the grayscale mean of the pure color display screen image in the ROI area to generate a grayscale mean array, including: Performing flattening correction processing on pixel points on the front collected image and the back collected image in the pure color display screen image; Calculate the grayscale mean of the flattened frontal captured image in the ROI area to generate a first grayscale mean array; Calculate the grayscale mean of the flattened back side captured image in the ROI area to generate a second grayscale mean array; A final grayscale mean array is calculated according to the first grayscale mean array and the second grayscale mean array in combination with the light transmittance weight of the transparent touch screen.

4. The method according to claim 3, characterized in that Inputting a pure color picture with gray scale g into the calibration screen, collecting it through the sampling camera, and generating a pure color display screen image, including: A pure color picture with a gray scale of g is inputted into the transparent touch screen, and the transparent touch screen is bent with a preset curvature; Performing back shading processing on the transparent touch screen; Using the acquisition camera to photograph the transparent touch screen to generate a front acquisition image; Performing front shading processing on the transparent touch screen; The transparent touch screen is photographed using the acquisition camera to generate a back acquisition image, and the front acquisition image and the front acquisition image are determined as pure color display screen images.

5. The method according to any one of claims 1 to 4, characterized in that After constructing a viewing angle unevenness model of the calibration screen at gray scale g according to the distance array and the correction coefficient set, the method further includes: Generate a correction coefficient map according to the spatial position relationship of each pixel point and the viewing angle unevenness model; Acquire an image to be corrected, and use the correction coefficient map to correct the image to be corrected to generate a corrected image; Calculate the grayscale mean corresponding to each ROI area in the corrected image and perform center normalization to obtain the corrected center normalized grayscale mean; The viewing angle non-uniformity model is evaluated according to the relative brightness of the image to be corrected, the centered normalized grayscale mean value and the reference brightness.

6. The method according to any one of claims 1 to 4, characterized in that Align the center position of the sampling camera with the center position of the calibration screen, where the calibration screen is of the same type as the display screen to be calibrated, including: Input the centering calibration pattern image into the calibration screen; The sampling camera is adjusted so that the center of the image formed by the sampling camera is aligned with the center of the crosshairs of the calibration screen.

7. A device for correcting uneven viewing angle of an image on a display screen, characterized in that: include: An alignment unit, used to align the center position of the sampling camera with the center position of the calibration screen, wherein the calibration screen is of the same type as the display screen to be calibrated; An input unit, used for inputting a viewing angle unevenness calibration picture with a gray scale of g into the calibration screen, wherein a plurality of ROI areas are distributed on the viewing angle unevenness calibration picture, and the ROI areas are determined by a colorimeter for performing detection; A first generating unit, configured to detect the ROI area on the calibration screen using the colorimeter to generate a brightness array; A second generating unit is used to input a pure color picture with a gray scale of g into the calibration screen, collect it through the sampling camera, and generate a pure color display screen image; A third generating unit is used to calculate the grayscale mean of the pure color display screen image in the ROI area to generate a grayscale mean array; a fourth generating unit, configured to perform centering normalization processing on the brightness array and the grayscale mean value array to generate normalized data, wherein the normalized data includes normalized brightness mean value data and normalized grayscale mean value data; A calculation unit, configured to calculate a correction coefficient set according to the normalized brightness mean data and the normalized grayscale mean data; A fifth generating unit, used for generating a set of distance arrays according to the relationship between the position of each ROI area and the center position; A construction unit is used to construct a viewing angle unevenness model of the calibration screen at gray scale g according to the distance array and the correction coefficient set.

8. The device according to claim 7, characterized in that The calibration screen is a bendable transparent touch screen, and the colorimeter includes a convex colorimeter and a concave colorimeter; The first generation unit comprises: The bendable transparent touch screen is bent with a preset curvature so that the front side of the transparent touch screen is located at the inner curved part; Using a convex colorimeter to detect the brightness of the ROI area on the front side of the transparent touch screen to generate a first initial brightness array; Using a concave colorimeter to detect the brightness of the ROI area on the back of the transparent touch screen to generate a second initial brightness array; A final brightness array is generated according to the first initial brightness array, the second initial brightness array and the light transmittance parameter of the transparent touch screen.

9. A system for correcting uneven viewing angle of a display screen image, characterized in that: include: A processor, a memory, an input-output unit and a bus, wherein the processor is connected to the memory, the input-output unit and the bus, the memory stores a program, and the processor calls the program to execute the method as claimed in any one of claims 1 to 6.

10. 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 6.

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