Compensation data determination method, compensation data determination system and storage device

Abstract

The present application discloses a compensation data determination method, a compensation data determination system and a storage device, the compensation data determination method comprising: obtaining first grayscale compensation data of a plurality of first display panels when displaying an image of a first preset grayscale respectively; obtaining target grayscale compensation data based on the plurality of first grayscale compensation data; wherein the target grayscale compensation data comprises a one-to-one corresponding grayscale compensation value interval and a target compensation gain coefficient, and there is no intersection between different grayscale compensation value intervals; obtaining the actual grayscale compensation value of the second display panel when displaying an image of the first preset grayscale; determining the target compensation gain coefficient corresponding to the grayscale compensation value interval in which the actual grayscale compensation value is located based on the target grayscale compensation data, and setting the actual compensation gain coefficient of the actual grayscale compensation value to the target compensation gain coefficient corresponding to the grayscale compensation value interval in which it is located. In the above manner, the present application can improve the mura repair efficiency of mass-produced products.

Description

Technical Field

[0001] The present application belongs to the field of display technology, and specifically relates to a compensation data determination method, a compensation data determination system and a storage device. Background Art

[0002] Panel mura mainly refers to the phenomenon of uneven brightness on the surface of the display panel when displaying grayscale images. The causes of this phenomenon may include dust, bad pixels, abnormal evaporation, etc. The solutions to mura usually include hardware repair methods and software repair methods.

[0003] Among them, hardware repair methods are generally used to improve the process; for example, strict control of evaporation conditions, routing optimization, TFT device design optimization, etc. Software repair methods generally use Demura algorithms to deal with mura. Software repair methods are faster, more flexible, and more cost-effective than hardware repair methods, so software repair methods are receiving more and more attention.

[0004] However, the current mura software repair for mass-produced products has the problem of low efficiency. Summary of the invention

[0005] The present application provides a compensation data determination method, a compensation data determination system and a storage device to improve the mura phenomenon of a display panel and improve the mura repair efficiency of mass-produced products.

[0006] In order to solve the above technical problems, a technical solution adopted in the present application is: providing a compensation data determination method, including: obtaining first grayscale compensation data of multiple first display panels when displaying images of a first preset grayscale respectively; obtaining target grayscale compensation data based on the multiple first grayscale compensation data; wherein the target grayscale compensation data includes one-to-one corresponding grayscale compensation value intervals and target compensation gain coefficients, and there is no intersection between different grayscale compensation value intervals; obtaining an actual grayscale compensation value of a second display panel when displaying an image of the first preset grayscale; wherein the second display panel and the first display panel are different display panels; determining the target compensation gain coefficient corresponding to the grayscale compensation value interval in which the actual grayscale compensation value is located based on the target grayscale compensation data, and setting the actual compensation gain coefficient of the actual grayscale compensation value to the target compensation gain coefficient corresponding to the grayscale compensation value interval in which it is located.

[0007] In order to solve the above technical problems, another technical solution adopted in the present application is: to provide a compensation data determination system, including: a carrier for carrying a display panel; an image acquisition device for acquiring images from the display surface of the display panel; a processor, coupled to the image acquisition device, for implementing the compensation data determination method described in any of the above embodiments.

[0008] In order to solve the above technical problems, another technical solution adopted by the present application is: providing a storage device storing program instructions that can be executed by a processor, wherein the program instructions are used to implement the compensation data determination method in any of the above embodiments.

[0009] Different from the prior art, the beneficial effect of the present application is that for multiple display panels produced from the same batch and the same model in the present application, multiple first display panels can be extracted as sample panels, and target grayscale compensation data can be obtained based on the first captured images of the multiple first display panels at the first preset grayscale. The target grayscale compensation data adopts a partitioning method, that is, different degrees of mura are classified according to the grayscale compensation value, and the same degree of mura corresponds to the same grayscale compensation value. Furthermore, for the remaining second display panels, their actual gain compensation coefficients can be set directly based on their actual grayscale compensation values ​​and target grayscale compensation data to improve the mura compensation effect and efficiency of mass-produced products. And when a second display panel has both lighter and heavier mura, the above design method can achieve the effect of successfully repairing different degrees of mura at one time. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work, among which:

[0011] Figure 1 This is a schematic diagram of the structure of an implementation scheme of a compensation data determination system of the present application;

[0012] Figure 2 This is a flow chart of an implementation method of compensation data determination method of the present application;

[0013] Figure 3 for Figure 2 A schematic flow chart of an implementation method corresponding to step S101;

[0014] Figure 4 A schematic diagram of an implementation of a normal grayscale brightness curve and a mura grayscale brightness curve;

[0015] Figure 5 is a schematic diagram of another implementation of a normal grayscale brightness curve and a mura grayscale brightness curve;

[0016] Figure 6 for Figure 2 A schematic diagram of a flow chart of an implementation method corresponding to step S102;

[0017] Figure 7 This is a schematic structural diagram of an implementation of a storage device of the present application. DETAILED DESCRIPTION

[0018] 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 embodiments of 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.

[0019] See also Figure 1 , Figure 1 It is a structural diagram of an embodiment of a compensation data determination system of the present application. The compensation data determination system includes: a carrier 10, an image acquisition device 12 and a processor 14; wherein, the carrier 10 is used to carry a display panel, and the carrier surface 100 of the carrier 10 for carrying the display panel has a high horizontality. The image acquisition device 12 is used to capture the display panel from the display surface side of the display panel; that is, the image acquisition device 12 is opposite to the bearing surface 100 of the carrier 10 and is arranged at a distance. Optionally, the image acquisition device 12 can be a CCD camera or the like. The processor 14 is coupled to the image acquisition device 12 for executing a subsequent compensation data determination method. Optionally, the image acquisition device 12 and the processor 14 can be coupled by wireless connection or wired connection.

[0020] In addition, in other embodiments, the compensation data determination system may further include other structures; for example, a sensor with a positioning function is located on the stage 10, and is used to locate the position of the display panel so that the display panel is placed at a preset position. For another example, a manipulator with a wiping function is used to wipe the display surface of the display panel before the image acquisition device 12 acquires images, so that the display surface of the display panel is free of dirt; and / or, the surface of the image acquisition device 12 facing the stage 10 is wiped, so that the surface of the image acquisition device 12 is free of dirt.

[0021] See also Figure 2 , Figure 2 This is a flow chart of an implementation method of the compensation data determination method of the present application. The execution subject of the compensation data determination method is Figure 1The processor 14 in the embodiment of the present invention, the compensation data determination method specifically includes:

[0022] S101: Obtaining first grayscale compensation data when a plurality of first display panels respectively display images of a first preset grayscale.

[0023] Specifically, see Figure 3 , Figure 3 for Figure 2 The specific implementation process of the above step S101 includes:

[0024] S201: Obtain a first captured image when each first display panel displays an image of a first preset gray scale.

[0025] Specifically, in this embodiment, the image of the first preset grayscale may be a red picture, a green picture, a blue picture, or the like, such as 16 grayscales, 32 grayscales, 64 grayscales, 128 grayscales, or 192 grayscales. Figure 1 The image acquisition device 12 in the image acquisition device 12 may acquire the first acquisition image by acquiring the first acquisition image from directly above the display surface of the first display panel. At this time, the first acquisition image may only include the imaging of the display area of ​​the first display panel; or the first acquisition image includes the imaging of the display area of ​​the first display panel, the frame imaging around the display area of ​​the first display panel, and the background imaging around the first display panel. When the first acquisition image includes the imaging of the display area of ​​the first display panel, the frame imaging around the display area of ​​the first display panel, and the background imaging around the first display panel, before entering the subsequent steps, the processor 14 may crop the first acquisition image to remove the frame imaging and the background imaging, so that the first acquisition image entering the subsequent steps only includes the imaging of the display area of ​​the first display panel.

[0026] S202: Obtain a normal brightness region and at least one abnormal brightness region from each first acquired image.

[0027] Specifically, the specific implementation process of the above step S202 can be: A. Based on the first preset grayscale, the corresponding normal brightness range can be obtained. B. For each pixel in the first acquired image, the actual brightness of each pixel is obtained; in response to the actual brightness of the pixel being outside the normal brightness range, the pixel is defined as a brightness abnormal pixel; in response to the actual brightness of the pixel being within the normal brightness range, the pixel is defined as a brightness normal pixel. C. When the proportion of brightness abnormal pixels in a certain area exceeds a preset value (for example, 90%, etc.), the area is defined as a brightness abnormal area (i.e., mura area).

[0028] In some cases, the brightness abnormal area can be gradual, for example, the closer to the normal brightness area, the higher the brightness, and the closer to the center of the brightness abnormal area, the darker. If the difference between the maximum brightness value and the minimum brightness value in the brightness abnormal area is greater than or equal to the first threshold, the subsequent demura effect may not be very good. In order to solve this problem, the brightness abnormal area with large brightness difference and large area can be subdivided into multiple brightness abnormal areas with smaller areas. At this time, the difference between the maximum brightness value and the minimum brightness value in each brightness abnormal area with smaller area after subdivision is less than the first threshold. Optionally, the brightness abnormal area with larger area can be subdivided into multiple annular brightness abnormal areas with smaller area, and the centers of multiple annular brightness abnormal areas with smaller area can coincide with the center of the brightness abnormal area with larger area before subdivision.

[0029] S203: Obtain brightness difference data based on the second brightness data of the normal brightness area and the first brightness data of the abnormal brightness area in the same first collected image.

[0030] Specifically, the first brightness data may be the average brightness of the corresponding brightness abnormal area, and the second brightness data may be the average brightness of the corresponding brightness normal area. The implementation process of the above step S203 may be: obtaining the difference between the second brightness data and the first brightness data, and the difference is the brightness difference data. Optionally, when the first brightness data of the brightness abnormal area is greater than the second brightness data of the brightness normal area, the difference is a negative number, and the brightness abnormal area is bright mura. When the first brightness data of the brightness abnormal area is less than the second brightness data of the brightness normal area, the difference is a positive number, and the brightness abnormal area is dark mura. The above process of obtaining brightness difference data based on average brightness is relatively simple, with a small amount of calculation, and can better reflect the brightness difference between the brightness abnormal area and the brightness normal area.

[0031] Of course, in other embodiments, the first brightness data may also be the median brightness of the corresponding abnormal brightness area, and the second brightness data may also be the median brightness of the corresponding normal brightness area, etc.

[0032] S204: Obtaining intermediate brightness data based on the brightness difference data and the second brightness data of each brightness abnormal area in the same first acquired image.

[0033] Specifically, the first brightness data is a value characterizing the brightness of the brightness abnormal area, and the second brightness data is a value characterizing the brightness of the normal brightness area. For example, the first brightness data is the average brightness of the corresponding brightness abnormal area, and the second brightness data is the average brightness of the corresponding brightness normal area. The brightness difference data can be the difference between the second brightness data and the first brightness data. The specific implementation process of the above step S204 can be: obtaining the first sum of the brightness difference data and the second brightness data of each brightness abnormal area, and the first sum is the intermediate brightness data. The process of obtaining the intermediate brightness data is relatively simple and the amount of calculation is low. Of course, in other embodiments, the implementation process of the above step S204 can also be other, for example, obtaining the product of the first coefficient and the difference between the second brightness data and the first brightness data, and obtaining the first sum of the product and the second brightness data. The size of the specific first coefficient can be artificially set to an empirical value.

[0034] S205: Determine first grayscale compensation data of the brightness abnormal area based on the intermediate brightness data and the second brightness data of each brightness abnormal area in the same first collected image, wherein the first grayscale compensation data includes a first grayscale compensation value and a first grayscale compensation coefficient.

[0035] Specifically, in one implementation, the specific implementation process of the above step S205 may be:

[0036] A. Obtaining an intermediate grayscale corresponding to the intermediate brightness data based on a normal grayscale brightness curve. Specifically, obtaining a grayscale corresponding to the intermediate brightness data on the normal grayscale brightness curve, the grayscale being the intermediate grayscale.

[0037] Specifically, see Figure 4 and Figure 5 , Figure 4 is a schematic diagram of an implementation of a normal grayscale brightness curve and a mura grayscale brightness curve, Figure 5 is a schematic diagram of another implementation of a normal grayscale brightness curve and a mura grayscale brightness curve; wherein, Figure 4 The corresponding is dark mura, that is, the brightness of the abnormal brightness area is lower than that of the normal brightness area. Figure 5 The corresponding is bright mura, that is, the brightness of the abnormal brightness area is greater than that of the normal brightness area. Figure 4 and Figure 5 The curve corresponding to the normal medium brightness area is the normal grayscale brightness curve, and the curve corresponding to the abnormal brightness area is the mura grayscale brightness curve; and the normal grayscale brightness curve can be pre-drawn based on the normal brightness area of ​​the display panel, and the mura grayscale brightness curve is drawn to illustrate the principle clearly, and the mura grayscale brightness curve will not be obtained during the actual processor operation process.

[0038] by Figure 4Taking dark mura as an example, assuming that when the display panel displays the first preset grayscale image, the grayscale of the normal display area is X, the brightness is L2, and the brightness of the abnormal display area is L1; after the above steps, the brightness difference data ΔL can be obtained as L2-L1, and at this time ΔL is greater than 0; the intermediate brightness data is L2+(L2-L1), at this time the intermediate brightness data is greater than the brightness of the normal display area, and the intermediate grayscale corresponding to the intermediate brightness data is X10, and X10 is greater than X.

[0039] by Figure 5 Taking bright mura as an example, assuming that when the display panel displays the first preset grayscale image, the grayscale of the normal display area is X′, the brightness is L2′, and the brightness of the abnormal display area is L1′; after the above steps, the brightness difference data ΔL′ can be obtained as L2′-L1′, and at this time ΔL′ is less than 0; the intermediate brightness data is L2′+(L2′-L1′), and at this time the intermediate brightness data is less than the brightness of the normal display area, and the intermediate grayscale corresponding to the intermediate brightness data is X10′, and X10′ is less than X.

[0040] B. Obtaining a first grayscale compensation value based on the middle grayscale and a first preset grayscale corresponding to the second brightness data.

[0041] Specifically, the first grayscale compensation value may be a difference between the middle grayscale and the first preset grayscale. Figure 4 Taking dark mura as an example, assuming that when the display panel displays a first preset grayscale image, the first grayscale compensation value is X10-X, and at this time the first grayscale compensation value is greater than 0, which indicates that the actual grayscale of the area needs to be increased to improve the brightness when compensating for dark mura. Figure 5 Taking bright mura as an example, assuming that when the display panel displays a first preset grayscale image, the first grayscale compensation value is X10′-X′, and at this time the first grayscale compensation value is less than 0, which indicates that the actual grayscale of the area needs to be reduced to reduce the brightness when compensating for bright mura later.

[0042] C. Determine a first grayscale compensation coefficient based on the first grayscale compensation value and the second brightness data; wherein the product of the first grayscale compensation value and the first grayscale compensation coefficient is rounded to be a final grayscale compensation value required to compensate for the brightness difference area.

[0043] Specifically, Figure 4 For example, if the first grayscale compensation value in step B is used for compensation, it can be found that on the mura brightness grayscale curve corresponding to the abnormal brightness area, the brightness corresponding to the middle grayscale X10 is still lower than the brightness L2 of the normal brightness area. Figure 5For example, if the first grayscale compensation value in step B is used for compensation, it can be found that on the mura brightness grayscale curve corresponding to the brightness abnormal area, the brightness corresponding to the intermediate grayscale X10′ will be lower than the brightness L2 of the brightness normal area. Therefore, it is necessary to enlarge or reduce the first grayscale compensation value by a certain proportion at this time, so that the difference between the display brightness of the subsequent brightness abnormal area after compensation with the final grayscale compensation value and the brightness of the brightness normal area is small. In addition, since the grayscales in the display panel are all in the form of integers, the product of the first grayscale compensation value and the first grayscale compensation coefficient needs to be rounded.

[0044] Optionally, the specific implementation process of the above step C can be: initialize the first grayscale compensation coefficient, that is, assign an initial value to the first grayscale compensation coefficient, for example, assign an initial value to the first grayscale compensation coefficient based on experience; obtain the first product of the first grayscale compensation value and the initialized first grayscale compensation coefficient, and perform an integer operation on the first product; make the display grayscale of the brightness abnormal area the third sum of the first preset grayscale and the first product; obtain the display brightness of the brightness abnormal area at this time; if the difference between the display brightness and the brightness of the normal display area is within the threshold range, output the first grayscale compensation coefficient; if the difference between the display brightness and the brightness of the normal display area is outside the threshold range, adjust the first grayscale compensation coefficient, and return to the step of obtaining the first product of the first grayscale compensation value and the first grayscale compensation coefficient, and perform an integer operation on the first product, until the difference between the display brightness and the brightness of the normal display area is within the threshold range. That is, the first grayscale compensation coefficient is obtained through multiple debugging.

[0045] Optionally, in this embodiment, the first grayscale compensation coefficient is greater than zero.

[0046] In an application scenario, Figure 4 Taking dark mura as an example, assuming that when the first display panel displays the first preset grayscale image, the first grayscale compensation value is X10-X, and after debugging, the corresponding first grayscale compensation coefficient is greater than 1. For example, the first grayscale compensation coefficient A1 is 1.05, 1.13, 1.35, etc., and the final grayscale compensation value is (X10-X)*A1. After the compensation operation, when the first display panel displays the first preset grayscale image, the grayscale data displayed in the abnormal brightness area is driven to be Figure 4 The grayscale data corresponding to X12.

[0047] In another application scenario, Figure 5Taking medium-brightness mura as an example, assuming that when the display panel displays the first preset grayscale image, the first grayscale compensation value is X10′-X′, and after debugging, the corresponding first grayscale compensation coefficient A1 is greater than 0 and less than 1. For example, the first grayscale compensation coefficient A1′ is 0.9, 0.85, 0.75, etc., and the final grayscale compensation value is (X10′-X′)*A1′, and X10′*A1′ corresponds to Figure 5 X12′ in the figure, and after the compensation operation, when the first display panel displays the first preset grayscale image, the grayscale data displayed in the abnormal brightness area is driven to be Figure 5 The grayscale data corresponding to X12′.

[0048] Of course, in other embodiments, other methods may be adopted to obtain the first grayscale compensation data. For example, based on the normal grayscale brightness curve, the first grayscale corresponding to the first brightness data and the second grayscale corresponding to the second brightness data are obtained; based on the first grayscale and the second grayscale, the first grayscale compensation value is obtained; based on the first grayscale compensation value and the second brightness data, the first grayscale compensation coefficient of the brightness abnormal area is determined.

[0049] S102: Obtain target grayscale compensation data based on a plurality of first grayscale compensation data, wherein the target grayscale compensation data includes grayscale compensation value intervals and target compensation gain coefficients corresponding to each other, and there is no intersection between different grayscale compensation value intervals. The target compensation gain coefficient is a coefficient for compensating the grayscale.

[0050] Specifically, see Figure 6 , Figure 6 for Figure 2 The flowchart of an implementation method corresponding to step S102 in FIG. 1 is a flowchart of an implementation method corresponding to step S102 in FIG. 1 , wherein step S102 specifically includes:

[0051] S301: Obtaining a grayscale compensation value interval in which a first grayscale compensation value in each first grayscale compensation data is located.

[0052] Specifically, mura of different degrees may be classified according to grayscales. The heavier the mura, the greater the first grayscale compensation value. Different grayscale levels may be set as needed, that is, corresponding to different numbers of grayscale compensation value intervals.

[0053] In an application scenario, Figure 4 The grayscale compensation value corresponding to medium and dark mura is divided into three grayscale compensation value intervals, for example, a grayscale compensation value interval of 1 to 5 corresponding to light mura, a grayscale compensation value interval of 6 to 10 corresponding to medium mura, and a grayscale compensation value interval of 11 to 20 corresponding to heavy mura. In other application scenarios, the grayscale compensation value interval corresponding to dark mura can also be set to more. The finer the division, the more accurate the control of the first grayscale compensation coefficient and the better the effect.

[0054] In another application scenario, Figure 5 The grayscale compensation value corresponding to medium-bright mura is divided into three grayscale compensation value intervals, for example, the grayscale compensation value interval corresponding to light mura is -(1 to 5), the grayscale compensation value interval corresponding to medium mura is -(6 to 10), and the grayscale compensation value interval corresponding to heavy mura is -(11 to 20). In other application scenarios, the grayscale compensation value interval corresponding to bright mura can also be set to more. The finer the division, the more accurate the control of the first grayscale compensation coefficient and the better the effect.

[0055] S302: performing normal distribution statistics on all first grayscale compensation coefficients belonging to the same grayscale compensation interval to obtain a target compensation gain coefficient corresponding to the grayscale compensation value interval.

[0056] Specifically, in this embodiment, after performing normal distribution statistics on all first grayscale compensation coefficients belonging to the same grayscale compensation interval, the first grayscale compensation coefficient with the highest probability of occurrence can be used as the target compensation gain coefficient corresponding to the grayscale compensation interval. Alternatively, the local mean of all first grayscale compensation coefficients in the range of μ1±t1*σ1 is obtained from normal distribution statistics, and the local mean is used as the target compensation gain coefficient; wherein μ1 is the overall mean of all first grayscale compensation coefficients in the current same grayscale compensation interval, σ1 is the variance, and t1 can be an arbitrarily selected positive integer. The above process of obtaining the target compensation gain coefficient based on normal distribution statistics is relatively simple, and the target compensation gain coefficient finally obtained can be well applied to all grayscale compensation values ​​in the grayscale compensation interval.

[0057] Optionally, the target compensation gain coefficient is a positive number, and the maximum value of the grayscale compensation value interval is positively correlated with the grayscale adjustment coefficient. This design method can better achieve grayscale compensation effects in different grayscale compensation value intervals.

[0058] For example, you can Figure 4 The grayscale compensation value corresponding to medium and dark mura is divided into three grayscale compensation value intervals. For example, the target compensation gain coefficient corresponding to the grayscale compensation value interval of 1 to 5 is 1.05 (corresponding to light mura), the target compensation gain coefficient corresponding to the grayscale compensation value interval of 6 to 10 is 1.13 (corresponding to medium mura), and the target compensation gain coefficient corresponding to the grayscale compensation value interval of 11 to 20 is 1.35 (corresponding to heavy mura). It can be seen that the first grayscale compensation value is a positive number, and the target compensation gain coefficient is greater than 1.

[0059] For example, you can Figure 5The grayscale compensation value corresponding to medium-bright mura is divided into three grayscale compensation value intervals. For example, the target compensation gain coefficient corresponding to the grayscale compensation value interval of -(1 to 5) is 0.9 (corresponding to light mura), the target compensation gain coefficient corresponding to the grayscale compensation value interval of -(6 to 10) is 0.85 (corresponding to medium mura), and the target compensation gain coefficient corresponding to the grayscale compensation value interval of -(11 to 20) is 0.75 (corresponding to heavy mura). It can be seen that the first grayscale compensation value is a negative number, and the target compensation gain coefficient is greater than 0 and less than 1.

[0060] S103: Obtaining an actual grayscale compensation value of the second display panel when displaying an image of a first preset grayscale; wherein the second display panel and the first display panel are different display panels.

[0061] Specifically, the first display panel and the second display panel belong to the same batch and the same model of display panels. The process of obtaining the actual grayscale compensation value in the above step S103 is the same as the process of obtaining the first grayscale compensation value in the first display panel, which will not be repeated here.

[0062] S104: determining a target compensation gain coefficient corresponding to the grayscale compensation value interval in which the actual grayscale compensation value is located based on the target grayscale compensation data, and setting the actual compensation gain coefficient of the actual grayscale compensation value to the target compensation gain coefficient corresponding to the grayscale compensation value interval in which the actual grayscale compensation value is located.

[0063] Specifically, it is assumed that the current second display panel includes at least one brightness abnormality area when displaying an image of a first preset grayscale; after obtaining the actual grayscale compensation value corresponding to each brightness abnormality area, the grayscale compensation value interval in which the actual grayscale compensation value is located is obtained, and then the actual compensation gain coefficient of the actual grayscale compensation value is directly set to the target compensation gain coefficient of the grayscale compensation value interval in which it is located.

[0064] In the above embodiment, the first display panel is equivalent to a sample plate of a display panel of the same model produced in the same batch as the second display panel. For example, assuming that one hundred thousand display panels of the same model are produced in the current batch, one thousand of them can be selected as the first display panel, and the rest can be selected as the second display panel. The mura phenomenon caused by the manufacturing process fluctuations of the first display panel and the second display panel is similar, so it is foreseeable to compensate the demura effect of the second display panel based on the target compensation gain coefficient of the first display panel. And the larger the number of sample plates, the more accurate the target compensation gain coefficient, and the better the demura effect of the target compensation gain coefficient obtained based on the sample plate is applicable to the second display panel, that is, the better the production effect of the mass production batch corresponding to the sample plate. And when there are both lighter and heavier mura on a second display panel, the above design method can achieve the effect of successfully repairing mura of different degrees at one time.

[0065] In addition, the above steps S101 to S104 correspond to a demura process at a first preset grayscale. It can be known that the above steps S101 to S104 can also be repeated, and the first preset grayscale of the compensation data determination method executed this time is different from the first preset grayscale of the compensation data determination method executed next time, so as to perform demura operations on the first display panel and the second display panel respectively at different first preset grayscales.

[0066] For example, in the present application, the monochrome R / G / B images corresponding to 16, 32, 64, 128, 192, etc. can be selected as the first preset grayscale images to obtain the target compensation gain coefficients under the monochrome R / G / B images corresponding to 16, 32, 64, 128, 192, etc. Further, in order to obtain the target compensation gain coefficients corresponding to the full grayscale (i.e., 0 to 255 grayscales), after obtaining the target compensation gain coefficients under the first preset grayscale, the target compensation gain coefficients under the remaining non-first preset grayscales can be obtained by using a linear difference method or the like.

[0067] In another embodiment, in order to facilitate direct calling in the subsequent display stage of the second display panel, after the above step S104, the above method further includes: for each pixel in the second display panel, when the second display panel displays the first preset grayscale image, the pixel is located in the abnormal brightness area, obtaining the rounded value of the product of the actual grayscale compensation value of the pixel and the actual compensation gain coefficient, and calculating the sum of the rounded value and the first preset grayscale to obtain the compensated grayscale of the first preset grayscale; burning the compensated grayscale of the first preset grayscale, the first preset grayscale, and the position information of the pixel. When the subsequent second display panel is displayed normally after leaving the factory, the image to be displayed in the second display panel can be obtained, and the target grayscale of each pixel in the image to be displayed can be obtained. Based on the target grayscale and position information, the corresponding second sum is directly retrieved from the burning information to perform compensation display. Of course, in other embodiments, the rounded value of the product of the actual grayscale compensation value of the pixel and the target compensation gain coefficient, the first preset grayscale, and the position information of the pixel can also be burned, and this application does not limit this.

[0068] In addition, the first display panel may be programmed with the first grayscale compensation data to achieve a better display effect of the first display panel.

[0069] See also Figure 7 , Figure 7This is a schematic diagram of the structure of an embodiment of a storage device of the present application. The storage device 30 stores program instructions 300 that can be executed by a processor, and the program instructions 300 are used to implement the evaluation method described in any of the above embodiments. Optionally, the storage device 30 may include: a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes.

[0070] The above description is only an embodiment of the present application and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly used in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A method for determining compensation data, characterized in that: include: Obtaining first grayscale compensation data when the plurality of first display panels respectively display images of a first preset grayscale; Obtaining target grayscale compensation data based on the plurality of first grayscale compensation data; wherein the first grayscale compensation data includes a first grayscale compensation value and a corresponding first grayscale compensation coefficient, and the target grayscale compensation data includes a one-to-one corresponding grayscale compensation value interval and a target compensation gain coefficient, and there is no intersection between different grayscale compensation value intervals; Obtaining an actual grayscale compensation value of the second display panel when displaying the image of the first preset grayscale; wherein the second display panel and the first display panel are different display panels; The target compensation gain coefficient corresponding to the grayscale compensation value interval in which the actual grayscale compensation value is located is determined based on the target grayscale compensation data, and the actual compensation gain coefficient of the actual grayscale compensation value is set as the target compensation gain coefficient corresponding to the grayscale compensation value interval in which it is located.

2. The compensation data determination method according to claim 1, characterized in that: The step of obtaining target grayscale compensation data based on the plurality of first grayscale compensation data comprises: Obtaining the grayscale compensation value interval in which the first grayscale compensation value in each of the first grayscale compensation data is located; Normal distribution statistics are performed on all the first grayscale compensation coefficients belonging to the same grayscale compensation value interval to obtain a target compensation gain coefficient corresponding to the grayscale compensation value interval.

3. The compensation data determination method according to claim 1 or 2, characterized in that: The target compensation gain coefficient is a positive number, and the maximum value of the grayscale compensation value interval is positively correlated with the target compensation gain coefficient.

4. The compensation data determination method according to claim 3, characterized in that: The first grayscale compensation value is a negative number, and the target compensation gain coefficient is greater than 0 and less than 1; and / or the first grayscale compensation value is a positive number, and the target compensation gain coefficient is greater than 1.

5. The compensation data determination method according to claim 1, characterized in that: The step of obtaining first grayscale compensation data when the first display panels respectively display images of the first preset grayscale comprises: Obtaining a first captured image when each of the first display panels displays the image at the first preset gray scale; Obtaining a normal brightness region and at least one abnormal brightness region from each of the first acquired images; Obtaining brightness difference data of each abnormal brightness area based on the second brightness data of the normal brightness area and the first brightness data of each abnormal brightness area in the same first acquired image; Obtaining intermediate brightness data based on the brightness difference data and the second brightness data of each of the brightness abnormal areas in the same first acquired image; The first grayscale compensation data of the brightness abnormal area is determined based on the intermediate brightness data and the second brightness data of each brightness abnormal area in the same first collected image.

6. The compensation data determination method according to claim 5, characterized in that: The step of determining the first grayscale compensation data of the abnormal brightness area based on the intermediate brightness data and the second brightness data of each abnormal brightness area in the same first acquired image comprises: Obtaining an intermediate grayscale corresponding to the intermediate brightness data based on a normal grayscale brightness curve; Obtaining a first grayscale compensation value based on the middle grayscale and a first preset grayscale corresponding to the second brightness data; A first grayscale compensation coefficient is determined based on the first grayscale compensation value and the second brightness data.

7. The compensation data determination method according to claim 5, characterized in that: The first brightness data is the average brightness of the abnormal brightness area, and the second brightness data is the average brightness of the normal brightness area; The brightness difference data is the difference between the second brightness data and the first brightness data; The intermediate brightness data is a first sum of the difference value and the second brightness data.

8. The compensation data determination method according to claim 5, characterized in that: The difference between the maximum brightness value and the minimum brightness value in the brightness abnormal area is less than a first threshold.

9. The compensation data determination method according to claim 1, after the step of determining the target compensation gain coefficient corresponding to the grayscale compensation value interval in which the actual grayscale compensation value is located based on the target grayscale compensation data, and setting the actual compensation gain coefficient of the actual grayscale compensation value as the target compensation gain coefficient corresponding to the grayscale compensation value interval in which the actual grayscale compensation value is located, the compensation data determination method further comprises: For each pixel in the second display panel, when the second display panel displays the first preset grayscale image, the pixel is located in the abnormal brightness area, the rounded value of the product of the actual grayscale compensation value of the pixel and the actual compensation gain coefficient is obtained, and the sum of the rounded value and the first preset grayscale is calculated to obtain the compensated grayscale of the first preset grayscale; the compensated grayscale of the first preset grayscale, the first preset grayscale, and the position information of the pixel are burned.

10. A compensation data determination system, characterized in that: include: A carrier, used for carrying a display panel; An image acquisition device, used for acquiring images from the display surface of the display panel to the display panel; A processor, coupled to the image acquisition device, is used to implement the compensation data determination method according to any one of claims 1 to 9.

11. A storage device, characterized in that: Program instructions that can be executed by a processor are stored, and the program instructions are used to implement the compensation data determination method according to any one of claims 1 to 9.

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