Display panel compensation method, mura identification method, device, equipment and medium

Abstract

This application discloses a display panel compensation method, mura identification method, apparatus, device, and medium. The display panel compensation method includes: setting multiple convolution kernels based on the characteristics of multiple mura types; wherein the multiple convolution kernels correspond one-to-one to the multiple mura types, and the numerical distribution characteristics of the convolution kernels are the same as the brightness distribution characteristics of the corresponding mura types; using each convolution kernel to perform a convolution operation on an initial compensation value matrix to obtain multiple extraction matrices; and compensating the display panel based on the initial compensation value matrix and the multiple extraction matrices. According to embodiments of the present application, the problem of under-compensation or over-compensation can be solved.

Description

Technical Field

[0001] The present application relates to the field of display technology, and in particular to a display panel compensation method, mura identification method, device, equipment and medium. Background Art

[0002] Due to differences in the manufacturing processes of each pixel in the display panel, the display panel has a mura problem, which causes different pixels of the display panel to have inconsistent brightness under the same grayscale and data voltage.

[0003] Compensation can be used to reduce the mura problem of a display panel. However, the compensation method in related art has problems of insufficient compensation or over-compensation. Summary of the Invention

[0004] Embodiments of the present application provide a display panel compensation method, mura identification method, device, equipment, and medium, which can solve the problem of insufficient compensation or overcompensation.

[0005] In a first aspect, an embodiment of the present application provides a display panel compensation method, comprising: setting multiple convolution kernels based on characteristics of multiple mura types; wherein the multiple convolution kernels correspond one-to-one to the multiple mura types, and the numerical distribution characteristics of the convolution kernels are the same as the brightness distribution characteristics of the corresponding mura types; using each convolution kernel to perform a convolution operation on an initial compensation value matrix to obtain multiple extraction matrices; and compensating the display panel based on the initial compensation value matrix and the multiple extraction matrices.

[0006] In one possible implementation of the first aspect, the number of rows and columns of the convolution kernel is positively correlated with the mura area of ​​the corresponding mura type. Thus, the numerical distribution characteristics of the convolution kernel are correlated with the mura area of ​​the mura type, so that convolution kernels of different sizes can be used to extract mura features of different sizes.

[0007] In a possible implementation of the first aspect, each convolution kernel is used to perform a convolution operation on the initial compensation value matrix to obtain multiple extraction matrices, including:

[0008] Fill the edges of the initial compensation value matrix;

[0009] According to the convolution step size of 1, each convolution kernel is used to perform convolution operation on the initial compensation value matrix after edge filling, so as to obtain multiple extraction matrices, and the number of rows and columns of each extraction matrix is ​​equal to the number of rows and columns of the initial compensation value matrix;

[0010] Preferably, edge filling is performed on the initial compensation value matrix, comprising:

[0011] The initial compensation value matrix is ​​edge-filled in a numerically symmetric manner.

[0012] By using edge padding, the numerical distribution pattern of the initial compensation value matrix can be avoided from being destroyed. Thus, the numerical features in the initial compensation value matrix can be more accurately extracted while ensuring that the number of rows and columns of the extraction matrix is ​​equal to that of the initial compensation value matrix. In addition, by setting the convolution step size to 1, every value in the initial compensation value matrix can be extracted, thereby more accurately extracting the numerical features in the initial compensation value matrix.

[0013] In a possible implementation of the first aspect, compensating a display panel according to an initial compensation value matrix and a plurality of extraction matrices includes:

[0014] Correcting each extraction matrix according to a preset correction factor corresponding to each extraction matrix;

[0015] The display panel is compensated according to the sum of the initial compensation value matrix and the plurality of corrected extraction matrices.

[0016] The extracted values ​​of the corresponding mura types extracted by the convolution kernel are corrected according to the correction coefficient and then superimposed on the initial compensation value matrix. This can better solve the problem of under-compensation or over-compensation of one or more mura types.

[0017] In a possible implementation of the first aspect, the display panel includes sub-pixels of multiple colors, and the multiple initial compensation value matrices correspond one-to-one to the sub-pixels of the multiple colors;

[0018] Preferably, the initial compensation value matrix includes any one of an initial grayscale compensation value matrix, an initial data voltage compensation value matrix, and an initial brightness compensation value matrix.

[0019] Since the multiple initial compensation value matrices correspond to the sub-pixels of multiple colors one-to-one, the sub-pixels of each color can be taken into consideration.

[0020] In a second aspect, based on the same inventive concept, an embodiment of the present application further provides a method for identifying mura of a display panel, comprising:

[0021] Setting a convolution kernel according to the characteristics of a preset mura type; wherein the numerical distribution characteristics of the convolution kernel are the same as the brightness distribution characteristics of the preset mura type;

[0022] Performing a convolution operation on the initial brightness value matrix of the display panel using a convolution kernel to obtain an extraction matrix;

[0023] It is determined whether the display panel has a preset mura type according to the numerical distribution characteristics in the extracted matrix.

[0024] In a third aspect, based on the same inventive concept, an embodiment of the present application further provides a compensation device for a display panel, comprising:

[0025] A first setting module is configured to set a plurality of convolution kernels according to characteristics of a plurality of mura types; wherein the plurality of convolution kernels correspond one-to-one to the plurality of mura types, and the numerical distribution characteristics of the convolution kernels are the same as the brightness distribution characteristics of the corresponding mura types;

[0026] A first operation module is used to perform convolution operation on the initial compensation value matrix using each convolution kernel to obtain multiple extraction matrices;

[0027] The compensation determination module is used to compensate the display panel according to the initial compensation value matrix and the multiple extraction matrices.

[0028] In a fourth aspect, based on the same inventive concept, an embodiment of the present application further provides a mura identification device for a display panel, comprising:

[0029] A second setting module is used to set a convolution kernel according to the characteristics of a preset mura type; wherein the numerical distribution characteristics of the convolution kernel are the same as the brightness distribution characteristics of the preset mura type;

[0030] A second operation module is used to perform a convolution operation on the initial brightness value matrix of the display panel using a convolution kernel to obtain an extraction matrix;

[0031] The mura determination module is used to determine whether a preset mura type exists on the display panel according to the distribution of values ​​in the extraction matrix.

[0032] In a fifth aspect, based on the same inventive concept, an embodiment of the present application further provides an electronic device, including:

[0033] A processor and a memory storing computer program instructions, wherein when the processor executes the computer program instructions, the display panel compensation method as described in any one of the embodiments of the first aspect is implemented, or the display panel mura identification method as described in the embodiment of the second aspect is implemented.

[0034] In a sixth aspect, based on the same inventive concept, an embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the display panel compensation method as described in any one of the embodiments of the first aspect is implemented, or the display panel mura identification method as described in the embodiment of the second aspect is implemented.

[0035] According to the display panel compensation method, apparatus, device, and medium provided by the embodiments of the present application, multiple convolution kernels are set to correspond one-to-one with multiple mura types. Since the numerical distribution characteristics of the convolution kernels are the same as the brightness distribution characteristics of the corresponding mura types, the numerical distribution characteristics in the extraction matrix obtained by the convolution operation will reflect the brightness distribution characteristics of the corresponding mura type. The display panel is compensated based on the initial compensation value matrix of the display panel and the multiple extraction matrices. This can take into account multiple mura types and improve or even eliminate the problem of undercompensation or overcompensation of one or more mura types. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Other features, objects and advantages of the present application will become more apparent by reading the following detailed description of non-limiting embodiments with reference to the accompanying drawings, in which the same or similar reference numerals represent the same or similar features and the accompanying drawings are not drawn to scale.

[0037] Figure 1 A schematic diagram showing a flow chart of a compensation method for a display panel provided by an embodiment of the present application;

[0038] Figure 2 A schematic diagram showing a type of mura of a display panel provided by an embodiment of the present application;

[0039] Figure 3 A schematic diagram of a convolution kernel provided by an embodiment of the present application is shown;

[0040] Figure 4 A schematic diagram showing another type of mura of a display panel provided by an embodiment of the present application;

[0041] Figure 5 A schematic diagram of a convolution kernel provided in another embodiment of the present application is shown;

[0042] Figure 6 A schematic diagram showing another type of mura of a display panel provided by an embodiment of the present application;

[0043] Figure 7 A schematic diagram showing a convolution kernel provided in yet another embodiment of the present application is shown;

[0044] Figure 8 A schematic diagram illustrating another type of mura of a display panel provided by an embodiment of the present application;

[0045] Figure 9 A schematic diagram showing a convolution kernel provided in yet another embodiment of the present application is shown;

[0046] Figure 10 A schematic diagram showing a flow chart of a compensation method for a display panel provided in another embodiment of the present application;

[0047] Figure 11 A schematic diagram illustrating a convolution operation in a compensation method for a display panel provided by an embodiment of the present application;

[0048] Figure 12 A schematic diagram illustrating edge filling in a compensation method for a display panel provided by an embodiment of the present application;

[0049] Figure 13 A schematic diagram showing a flow chart of a compensation method for a display panel provided in yet another embodiment of the present application;

[0050] Figure 14 A schematic diagram illustrating a flow chart of a method for identifying mura of a display panel provided by an embodiment of the present application is shown;

[0051] Figure 15 A schematic diagram showing a numerical matrix in a mura identification method for a display panel provided by an embodiment of the present application;

[0052] Figure 16 A schematic structural diagram of a compensation device for a display panel provided by an embodiment of the present application is shown;

[0053] Figure 17 A schematic structural diagram of a mura identification device for a display panel provided by an embodiment of the present application is shown;

[0054] Figure 18 A schematic structural diagram of an electronic device provided by an embodiment of the present application is shown. DETAILED DESCRIPTION

[0055] The features and exemplary embodiments of various aspects of the present application will be described in detail below. In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only configured to explain the present application and are not configured to limit the present application. For those skilled in the art, the present application can be implemented without the need for some of these specific details. The following description of the embodiments is merely to provide a better understanding of the present application by illustrating the examples of the present application.

[0056] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, the elements defined by the phrase "comprising..." do not exclude the presence of other identical elements in the process, method, article, or device comprising the elements.

[0057] It should be understood that when describing the structure of a component, when a layer or a region is referred to as being "on" or "over" another layer or region, it may mean that it is directly on the other layer or region, or that other layers or regions are included between it and the other layer or region. Furthermore, if the component is turned over, the layer or region will be "below" or "beneath" the other layer or region.

[0058] It should be understood that the term "and / or" as used herein is merely a description of the relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A exists alone, A and B exist simultaneously, or B exists alone. Furthermore, the character " / " in this document generally indicates that the associated objects are in an "or" relationship.

[0059] It will be apparent to those skilled in the art that various modifications and variations can be made in this application without departing from the spirit or scope of this application. Therefore, this application is intended to cover modifications and variations of this application that fall within the scope of the corresponding claims (technical solutions claimed for protection) and their equivalents. It should be noted that the embodiments provided in the examples of this application can be combined with each other without contradiction.

[0060] Before describing the technical solutions provided by the embodiments of the present application, in order to facilitate understanding of the embodiments of the present application, the present application first specifically describes the problems existing in the related art:

[0061] As described in the background, the inventors discovered through extensive research that multiple types of mura can be found in actual products, such as S-direction mura (vertical stripes), G-direction mura (horizontal stripes), diagonal mura, and black or white spots. These mura types are caused by distinct mechanisms and display levels at varying grayscale levels. Related technologies often utilize the same mura compensation algorithm, resulting in adequate compensation for one mura type and insufficient or overcompensation for one or more other mura types.

[0062] To address the above-mentioned issues, embodiments of the present application provide a display panel compensation method, mura identification method, device, equipment, and medium. The following describes various embodiments of the display panel compensation method, mura identification method, device, equipment, and medium in conjunction with the accompanying drawings.

[0063] The following first introduces the compensation method for the display panel provided by the embodiment of the present application.

[0064] For example, the display panel in the embodiment of the present application may be an organic light emitting diode (OLED) display panel, and of course may be other types of display panels, which is not limited in the present application.

[0065] like Figure 1 As shown, the display panel compensation method provided in the embodiment of the present application may include steps S110 to S130.

[0066] S110, setting a plurality of convolution kernels according to characteristics of the plurality of mura types; wherein the plurality of convolution kernels correspond one-to-one to the plurality of mura types, and the numerical distribution characteristics of the convolution kernels are the same as the brightness distribution characteristics of the corresponding mura types;

[0067] S120, using each convolution kernel to perform a convolution operation on the initial compensation value matrix to obtain multiple extraction matrices;

[0068] S130 , compensating the display panel according to the initial compensation value matrix and the multiple extraction matrices.

[0069] The specific implementation of each of the above steps will be described in detail below.

[0070] According to the display panel compensation method provided in the embodiments of the present application, multiple convolution kernels are set to correspond one-to-one with multiple mura types. Since the numerical distribution characteristics of the convolution kernels are the same as the brightness distribution characteristics of the corresponding mura types, the numerical distribution characteristics in the extraction matrix obtained by the convolution operation will reflect the brightness distribution characteristics of the corresponding mura type. The display panel is compensated based on the initial compensation value matrix of the display panel and the multiple extraction matrices. In this way, multiple mura types can be taken into account, and the problem of undercompensation or overcompensation of one or more mura types can be improved or even eliminated.

[0071] For example, in S110 , the multiple mura types may include, for example, S-direction mura (vertical mura), G-direction mura (horizontal mura), diagonal mura, black spots or white spots mura, and the like.

[0072] For example, the convolution kernel corresponding to each mura type may be set as follows: The sum of all values ​​in the convolution kernel is 0.

[0073] In this article, the first direction X is taken as the row direction and the second direction Y is taken as the column direction. Figure 2 As shown, Figure 2 The mura type shown is G-direction mura. The brightness distribution characteristics of G-direction mura include differences in the brightness of mura region Q21 and its adjacent upper region Q22 and lower region Q23. For example, the brightness of upper region Q22 and lower region Q23 can be considered the same.

[0074] For example, the convolution kernel includes a matrix form, which can be as follows: Figure 3 The convolution kernel corresponding to G-direction mura is set in the following manner. Based on the brightness distribution characteristics of the G-direction mura, where the brightness of the mura area is different from that of the adjacent areas above and below, the number of rows and columns of the convolution kernel corresponding to G-direction mura can be set first. Then, a value is assigned to each position in the convolution kernel so that the values ​​of the positions in the middle rows are different from the values ​​of the positions in the adjacent rows above and below, while the values ​​of the positions in the upper and lower rows can be the same.

[0075] In order to better understand the setting of convolution kernel, such as Figure 3As shown, for example, the number of rows and columns of the convolution kernel corresponding to G-direction mura is 49. For example, the number of rows in the middle is 3, and the number of rows above and below is 23. The value of each position in the 3 rows and 49 columns of the middle area can be 1 / (3*49), the value of each position in the 23 rows and 49 columns of the upper area can be -1 / (46*49), and the value of each position in the 23 rows and 49 columns of the lower area can also be -1 / (46*49). In this way, the sum of all values ​​in the convolution kernel is 0, and the value distribution characteristics are the same as the brightness distribution characteristics of G-direction mura.

[0076] like Figure 4 As shown, Figure 4 The mura type shown is S-direction mura. The brightness distribution characteristics of S-direction mura include differences in the brightness of mura region Q41 and its adjacent left region Q42 and right region Q43. For example, the brightness of left region Q42 and right region Q43 can be considered the same.

[0077] Similarly, you can follow Figure 5 The convolution kernel corresponding to S-direction mura is set in the following manner. Based on the brightness distribution characteristics of the mura area in the S-direction mura, which differs from the brightness of the adjacent left and right areas, the number of rows and columns of the convolution kernel corresponding to the S-direction mura can be set first. Then, a value is assigned to each position in the convolution kernel so that the values ​​of the positions in the middle columns are different from the values ​​of the positions in the adjacent left and right columns, while the values ​​of the positions in the left and right columns can be the same.

[0078] In order to better understand the setting of convolution kernel, such as Figure 5 As shown, for example, the number of rows and columns of the convolution kernel corresponding to S-direction mura is 49. For example, the number of columns in the middle is 3, and the number of columns on the left and right are 23. The value of each position in the 3 columns and 49 rows of the middle area can be 1 / (3*49), the value of each position in the 23 columns and 49 rows of the left area can be -1 / (46*49), and the value of each position in the 23 columns and 49 rows of the right area can also be -1 / (46*49). In this way, the sum of all values ​​in the convolution kernel is 0, and the value distribution characteristics are the same as the brightness distribution characteristics of S-direction mura.

[0079] like Figure 6 As shown, Figure 6 The mura type shown is black or white mura. The brightness distribution characteristics of black or white mura include a difference in brightness between the mura area Q61 and the surrounding area Q62. For example, the brightness of the surrounding area Q62 can be considered to be the same.

[0080] Similarly, you can follow Figure 7The convolution kernel corresponding to black or white mura is set in the following manner. Based on the brightness distribution characteristic of the mura area in black or white mura, which differs from the brightness of the surrounding area, the number of rows and columns of the convolution kernel corresponding to black or white mura can be set first. Then, a value is assigned to each position in the convolution kernel, so that the value at the center is different from the values ​​at the surrounding areas, while the values ​​at the surrounding areas can be the same.

[0081] In order to better understand the setting of convolution kernel, such as Figure 7 As shown, the number of rows and columns of the convolution kernel corresponding to black or white spot mura is 49. For example, the number of rows and columns in the central area is 5. The value of each position in the 5 rows and 5 columns of the central area can be 1 / (5*5), and the value of each position in the surrounding area can be -1 / (49*49-25). In this way, the sum of all values ​​in the convolution kernel is 0, and the value distribution characteristics are the same as the brightness distribution characteristics of black or white spot mura.

[0082] like Figure 8 As shown, Figure 8 The mura type shown is diagonal mura. The brightness distribution characteristics of diagonal mura include differences between the brightness of mura region Q81 and its adjacent upper left region Q82 and lower right region Q83. For example, the brightness of the upper left region Q82 and the lower right region Q83 can be considered the same.

[0083] Similarly, you can follow Figure 9 The convolution kernel corresponding to diagonal mura is set in the following manner. Based on the brightness distribution characteristics of diagonal mura, where the brightness of the mura area is different from that of the adjacent upper left and lower right areas, the number of rows and columns of the convolution kernel corresponding to diagonal mura can be set first. Then, a value is assigned to each position in the convolution kernel so that the value of the diagonal center position is different from that of the adjacent upper left and lower right areas, while the values ​​of the upper left and lower right areas can be the same.

[0084] In order to better understand the setting of convolution kernel, such as Figure 9 As shown in the figure, since the mura area in twill mura is small, the number of rows and columns of the convolution kernel corresponding to twill mura can both be 15. For example, the value of each position in the twill area can be 1 / (15*15-14*14), and the values ​​of the upper left area and the lower right area can both be -1 / (14*14). In this way, the sum of all values ​​in the convolution kernel is 0, and the value distribution characteristics are the same as the brightness distribution characteristics of twill mura.

[0085] The values ​​in the above examples are merely examples and are not intended to limit this application. For example, the number of rows and columns of the convolution kernel corresponding to each mura type and the specific values ​​in the convolution kernel can be set according to actual conditions, as long as the numerical distribution characteristics of the convolution kernel are consistent with the brightness distribution characteristics of the corresponding mura type.

[0086] As an optional embodiment, before S110 , the display panel compensation method provided in the embodiment of the present application may further include: determining a mura type existing in the display panel.

[0087] For example, determining the mura type of the display panel may specifically include: causing the display panel to display a grayscale image to be tested, then obtaining the brightness of each pixel of the display panel, and determining the mura type of the display panel based on the brightness of each pixel.

[0088] In some optional embodiments, the number of rows and columns of the convolution kernel is positively correlated with the mura area of ​​the corresponding mura type. For example, for G-direction mura, if the area of ​​the mura region is large, the number of rows and columns of the convolution kernel corresponding to the G-direction mura can be set to be larger. For another example, for G-direction mura, if the mura region is narrower than its adjacent upper and lower regions, the number of rows in the middle region of the convolution kernel corresponding to the G-direction mura can be set to be smaller.

[0089] Different mura types correspond to different convolution kernels. In other words, the numerical distribution characteristics of the convolution kernel are related to the shape of the mura within the mura type. In this embodiment, the number of rows and columns of the convolution kernel is further set to be positively correlated with the mura area of ​​the corresponding mura type. This way, the numerical distribution characteristics of the convolution kernel are correlated with the mura area, shape, and width of the mura type. This allows the use of convolution kernels of different sizes to extract mura features of varying sizes.

[0090] In some optional embodiments, such as Figure 10 As shown, S120 may specifically include S121 and S122.

[0091] S121, performing edge filling on the initial compensation value matrix.

[0092] S122 , performing convolution operations on the initial compensation value matrix after edge filling using each convolution kernel with a convolution step of 1, to obtain multiple extraction matrices, wherein the number of rows and columns of each extraction matrix is ​​equal to the number of rows and columns of the initial compensation value matrix.

[0093] Since the area of ​​the mura region in the display panel is usually not too large relative to the entire display area, the number of rows and columns of the convolution kernel will be smaller than the number of rows and columns of the display panel pixels. The number of rows and columns of the display panel pixels can be equal to the number of rows and columns of the initial compensation value matrix. In other words, the number of rows and columns of the convolution kernel can be smaller than the number of rows and columns of the initial compensation value matrix, and even the number of rows and columns of the convolution kernel can be much smaller than the number of rows and columns of the initial compensation value matrix.

[0094] In order to superimpose each extraction matrix with the initial compensation value matrix in the subsequent steps, the number of rows and columns of the extraction matrix needs to be equal to the number of rows and columns of the initial compensation value matrix. Since the number of rows and columns of the convolution kernel is less than the number of rows and columns of the initial compensation value matrix, it is necessary to fill the initial compensation value matrix. By filling the edges, it is possible to avoid destroying the numerical distribution law of the initial compensation value matrix, thereby more accurately extracting the numerical features in the initial compensation value matrix when the number of rows and columns of the extraction matrix needs to be equal to the number of rows and columns of the initial compensation value matrix. In addition, by setting the convolution step size to 1, each value in the initial compensation value matrix can be extracted, thereby more accurately extracting the numerical features in the initial compensation value matrix.

[0095] For example, the convolution operation process can be to scan the convolution kernel in sequence at all positions of the initial compensation value matrix, multiply the values ​​at the corresponding positions and then add them. Figure 11 As shown, taking the initial compensation value matrix with 8 rows and columns and the convolution kernel with 3 rows and columns as an example, for example, when the convolution kernel scans the initial compensation value matrix The value obtained by the convolution operation is (-1*3)+(0*0)+(1*1)+(-2*2)+(0*6)+(2*2)+(-1*2)+(0*4)+(1*1)=-3.

[0096] These values ​​are just examples and are not intended to limit the present application.

[0097] Optionally, S121 may specifically include: performing edge filling on the initial compensation value matrix in a numerically symmetric manner.

[0098] like Figure 12 As shown, still taking the example that the number of rows and columns of the initial compensation value matrix are both 8, for example, if 2 rows need to be filled at the edge, the values ​​of the 2 filled rows and the values ​​of the first row and the second row in the initial compensation value matrix can be symmetrical about the edge of the initial compensation value matrix. Figure 12 The dashed box represents the filled one, and the solid box represents the initial compensation value matrix.

[0099] The number of rows and columns for edge filling can be determined based on actual conditions, and this application does not impose any limitation on this.

[0100] In some optional embodiments, such as Figure 13As shown, S130 may specifically include S131 and S132.

[0101] S131, correcting each extraction matrix according to a preset correction coefficient corresponding to each extraction matrix;

[0102] S132 , compensating the display panel according to the sum of the initial compensation value matrix and the multiple corrected extraction matrices.

[0103] For example, a preset correction coefficient corresponding to each extraction matrix can be set based on experience. For example, a number of candidate correction coefficients can be set, and the compensation effect under each candidate correction coefficient can be tested. The candidate correction coefficient corresponding to the compensation effect that meets the preset requirements is selected, and the candidate correction coefficient that meets the preset requirements is used as the final correction coefficient.

[0104] It is understandable that if the preset correction coefficient is greater than 0, the compensation will be strengthened, and if the preset correction coefficient is less than 0, the compensation will be weakened.

[0105] For example, the target value matrix A' is obtained by summing the initial compensation value matrix with multiple corrected extraction matrices. Assuming the display panel has two mura types, two extraction matrices can be obtained. Then, A' = A + ratio_s * As + ratio_g * Ag, where A represents the initial compensation value matrix, As represents the extraction matrix corresponding to one mura type, ratio_s represents the correction coefficient corresponding to the extraction matrix As, Ag represents the extraction matrix corresponding to the other mura type, and ratio_g represents the correction coefficient corresponding to the extraction matrix Ag.

[0106] In the embodiment of the present application, the extracted value of the corresponding mura type extracted by the convolution kernel is corrected according to the correction coefficient and then superimposed on the initial compensation value matrix, which can better solve the problem of insufficient compensation or overcompensation of one or more mura types.

[0107] For example, the initial compensation value matrices at different grayscales may be different, and the correction coefficients at different grayscales may also be different.

[0108] For example, the display panel may have multiple brightness levels, and different brightness levels may correspond to different positions of the brightness adjustment bar. The initial compensation value matrix at different brightness levels may be different, and the correction coefficients at different brightness levels may also be different.

[0109] In some optional embodiments, the display panel includes sub-pixels of multiple colors, and the multiple initial compensation value matrices correspond one-to-one to the sub-pixels of the multiple colors. For example, the display panel may include red sub-pixels, blue sub-pixels, and green sub-pixels. The number of initial compensation value matrices may be three, namely, an initial compensation value matrix corresponding to the red sub-pixels, an initial compensation value matrix corresponding to the blue sub-pixels, and an initial compensation value matrix corresponding to the green sub-pixels.

[0110] Optionally, the initial compensation value matrix may include any one of an initial grayscale compensation value matrix, an initial data voltage compensation value matrix, and an initial brightness compensation value matrix.

[0111] The present application does not limit the method for determining the initial compensation value matrix. For example, the initial compensation value matrix can be determined using any compensation method.

[0112] Based on the same inventive concept, the embodiment of the present application also provides a method for identifying mura of a display panel. Figure 14 As shown, the method for identifying mura of a display panel provided in an embodiment of the present application may include S410 to S430.

[0113] S410, setting a convolution kernel according to a characteristic of a preset mura type; wherein a numerical distribution characteristic of the convolution kernel is the same as a brightness distribution characteristic of the preset mura type;

[0114] S420, performing a convolution operation on the initial brightness value matrix of the display panel using a convolution kernel to obtain an extraction matrix;

[0115] S430: Determine whether a preset mura type exists on the display panel according to the extracted matrix.

[0116] For example, if you want to determine whether the display panel has G-direction mura, the preset mura type can be G-direction mura. Similarly, if you want to determine whether the display panel has S-direction mura, black or white spot mura, diagonal mura, etc., the preset mura type can be S-direction mura, black or white spot mura, diagonal mura, etc.

[0117] The convolution kernel can be set by referring to the above description of the setting method of the convolution kernel, which will not be described in detail here. In addition, the convolution operation can be performed by referring to the above description of the convolution operation, which will not be described in detail here.

[0118] For example, in S420, the initial brightness value matrix can be understood as the initial brightness value matrix of the display panel before compensation. In the embodiment of the present application, a convolution operation is performed on the initial brightness value matrix of the display panel before compensation to determine whether the display panel has a preset mura type.

[0119] For example, in S430, if an extreme value exists in the extraction matrix, it can be determined that the display panel has a preset mura type. If no extreme value exists in the extraction matrix, it can be determined that the display panel does not have the preset mura type. An extreme value can be understood as a value that differs significantly from other values ​​in the extraction matrix.

[0120] In order to better understand how to determine whether there is a preset mura type based on the extraction matrix, take the preset mura type as G-direction mura as an example. Figure 15 As shown, taking the display panel including 10 rows and 6 columns of pixels as an example, the initial brightness value matrix also has 10 rows and 6 columns of values. For example, if the display panel has G-direction mura, the brightness of the third row is brighter, for example, the brightness of the third row is 4, and the brightness of other rows is 1. The matrix corresponding to the set convolution kernel is During the convolution operation, when the convolution kernel scans the mura area (i.e., the third row), for example, when the second row of the convolution kernel is aligned with the third row of the initial brightness value matrix, the value of the convolution operation is (-1*1)+(-1*1)+(-1*1)+(2*4)+(2*4)+(2*4)+(-1*1)+(-1*1)+(-1*1)=18. When the convolution kernel scans the non-mura area, for example, when all values ​​of the convolution kernel are aligned with the value of 1 in the initial brightness value matrix, the value of the convolution operation is (-1*1)+(-1*1)+(-1*1)+(2*1)+(2*1)+(2*1)+(-1*1)+(-1*1)+(-1*1)=0.

[0121] It can be understood that 18 is the extreme value in the extraction matrix.

[0122] For example, when the display panel does not have mura, ideally, the brightness of each pixel of the display panel is equal, so the values ​​in the obtained extraction matrix are also equal, that is, there is no extreme value in the extraction matrix.

[0123] The above only uses G-direction mura as an example. Similarly, S-direction mura, diagonal mura, black spots or white spots mura, etc. can also be identified.

[0124] According to the display panel mura identification method provided by the embodiment of the present application, it is possible to accurately determine whether a preset mura type exists in the display panel.

[0125] For example, when a preset mura type exists on the display panel, the position of the mura area may be determined according to the distribution position of the values ​​in the extraction matrix.

[0126] For example, if a display panel has a preset mura type, the preset mura type of the display panel can be graded based on the extreme value in the extraction matrix. For example, a larger extreme value indicates a more severe mura level for the preset mura type, while a smaller extreme value indicates a milder mura level for the preset mura type.

[0127] Based on the same inventive concept, the embodiment of the present application also provides a compensation device for a display panel. Figure 16 As shown, the compensation device 600 for a display panel provided in an embodiment of the present application may include a first setting module 601 , a first operation module 602 and a compensation determination module 603 .

[0128] A first setting module 601 is configured to set a plurality of convolution kernels according to characteristics of a plurality of mura types; wherein the plurality of convolution kernels correspond one-to-one to the plurality of mura types, and the numerical distribution characteristics of the convolution kernels are the same as the brightness distribution characteristics of the corresponding mura types;

[0129] A first operation module 602 is configured to perform a convolution operation on the initial compensation value matrix using each convolution kernel to obtain multiple extraction matrices;

[0130] The compensation determination module 603 is configured to compensate the display panel according to the initial compensation value matrix and the plurality of extraction matrices.

[0131] According to the display panel compensation device provided in the embodiments of the present application, multiple convolution kernels are provided in one-to-one correspondence with multiple mura types. Since the numerical distribution characteristics of the convolution kernels are identical to the brightness distribution characteristics of the corresponding mura types, the numerical distribution characteristics in the extraction matrix obtained by the convolution operation will reflect the brightness distribution characteristics of the corresponding mura type. The display panel is compensated based on the initial compensation value matrix of the display panel and the multiple extraction matrices. This can take into account multiple mura types and improve or even eliminate the problem of undercompensation or overcompensation of one or more mura types.

[0132] In some optional embodiments, the number of rows and columns of the convolution kernel is positively correlated with the mura area of ​​the corresponding mura type.

[0133] In some optional embodiments, the first operation module 602 may be specifically configured to:

[0134] Fill the edges of the initial compensation value matrix;

[0135] According to the convolution step size of 1, each convolution kernel is used to perform convolution operation on the initial compensation value matrix after edge filling, so as to obtain multiple extraction matrices, and the number of rows and columns of each extraction matrix is ​​equal to the number of rows and columns of the initial compensation value matrix;

[0136] In some optional embodiments, the first operation module 602 may be specifically configured to:

[0137] The initial compensation value matrix is ​​edge-filled in a numerically symmetric manner.

[0138] In some optional embodiments, the compensation determination module 603 may be specifically configured to:

[0139] Correcting each extraction matrix according to a preset correction factor corresponding to each extraction matrix;

[0140] The display panel is compensated according to the sum of the initial compensation value matrix and the plurality of corrected extraction matrices.

[0141] In some optional embodiments, the display panel includes sub-pixels of multiple colors, and the multiple initial compensation value matrices correspond one-to-one to the sub-pixels of the multiple colors;

[0142] Optionally, the initial compensation value matrix includes any one of an initial grayscale compensation value matrix, an initial data voltage compensation value matrix, and an initial brightness compensation value matrix.

[0143] The compensation device for the display panel provided in the embodiment of the present application can achieve Figure 1 To avoid repetition, the various processes in the embodiment of the compensation method for a display panel are not described again here.

[0144] Based on the same inventive concept, the embodiment of the present application also provides a mura identification device for a display panel. Figure 17 As shown, the display panel mura identification device 700 provided in the embodiment of the present application may include a second setting module 701 , a second operation module 702 and a mura determination module 703 .

[0145] A second setting module 701 is configured to set a convolution kernel according to a characteristic of a preset mura type; wherein the numerical distribution characteristic of the convolution kernel is the same as the brightness distribution characteristic of the preset mura type;

[0146] A second operation module 702 is configured to perform a convolution operation on the initial brightness value matrix of the display panel using a convolution kernel to obtain an extraction matrix;

[0147] The mura determination module 703 is configured to determine whether a preset mura type exists on the display panel according to the value distribution in the extraction matrix.

[0148] According to the mura identification device for a display panel provided in the embodiment of the present application, it is possible to accurately determine whether a preset mura type exists on the display panel.

[0149] For example, when a preset mura type exists on the display panel, the position of the mura area may be determined according to the distribution position of the values ​​in the extraction matrix.

[0150] For example, if a display panel has a preset mura type, the preset mura type of the display panel can be graded based on the extreme value in the extraction matrix. For example, a larger extreme value indicates a more severe mura level for the preset mura type, while a smaller extreme value indicates a milder mura level for the preset mura type.

[0151] The mura identification device for a display panel provided in the embodiment of the present application can achieve Figure 14 To avoid repetition, each process in the embodiment of the method for identifying mura of a display panel will not be described again here.

[0152] The compensation device of the display panel and the mura identification device of the display panel in the embodiment of the present application can be a device, or a component, integrated circuit, or chip in a terminal. The device can be a mobile electronic device or a non-mobile electronic device. For example, the mobile electronic device can be a mobile phone, a tablet computer, a laptop computer, a PDA, an in-vehicle electronic device, a wearable device, an ultra-mobile personal computer (UMPC), a netbook or a personal digital assistant (PDA), etc., and the non-mobile electronic device can be a server, a network attached storage (NAS), a personal computer (PC), a television (TV), an ATM or a self-service machine, etc., which is not specifically limited in the embodiment of the present application.

[0153] Figure 18 A schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present application is shown.

[0154] The electronic device may include a processor 801 and a memory 802 storing computer program instructions.

[0155] Specifically, the processor 801 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiment of the present invention.

[0156] The memory 802 may include a large-capacity memory for data or instructions. By way of example and not limitation, the memory 802 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive, or a combination of two or more of these. Where appropriate, the memory 802 may include a removable or non-removable (or fixed) medium. Where appropriate, the memory 802 may be inside or outside the integrated gateway disaster recovery device. In a specific embodiment, the memory 802 is a non-volatile solid-state memory. In a specific embodiment, the memory 802 includes a read-only memory (ROM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), an electrically rewritable ROM (EAROM), or a flash memory, or a combination of two or more of these. Exemplarily, the memory may include a non-volatile transient memory.

[0157] The processor 801 reads and executes computer program instructions stored in the memory 802 to implement any one of the display panel compensation methods or display panel mura identification methods in the above embodiments.

[0158] In one example, the electronic device may further include a communication interface 803 and a bus 810. Figure 18 As shown, the processor 801, the memory 802, and the communication interface 803 are connected via a bus 810 and communicate with each other.

[0159] The communication interface 803 is mainly used to implement communication between various modules, devices, units and / or equipment in the embodiment of the present invention.

[0160] Bus 810 comprises hardware, software or both, couples the parts of electronic equipment to each other.For example, and not limitation, bus can comprise accelerated graphics port (AGP) or other graphics bus, enhanced industry standard architecture (EISA) bus, front side bus (FSB), hypertransport (HT) interconnection, industry standard architecture (ISA) bus, infinite bandwidth interconnection, low pin count (LPC) bus, memory bus, micro channel architecture (MCA) bus, peripheral component interconnection (PCI) bus, PCI-Express (PCI-X) bus, serial advanced technology attachment (SATA) bus, video electronics standard association local (VLB) bus or other suitable bus or two or more of these combinations.In suitable cases, bus 810 can comprise one or more buses.Although the embodiment of the present invention describes and shows specific bus, the present invention considers any suitable bus or interconnection.

[0161] The electronic device can execute the display panel compensation method or the display panel mura identification method in the embodiment of the present application, thereby realizing the combination of Figure 1 and Figure 16 The display panel compensation method and display panel compensation device described herein, or the combination thereof Figure 14 and Figure 17 A method for identifying mura of a display panel and a device for identifying mura of a display panel are described.

[0162] The present application also provides a computer-readable storage medium having a computer program stored thereon. When executed by a processor, the computer program can implement the display panel compensation method or display panel mura identification method described in the above-described embodiments, achieving the same technical effects. To avoid repetition, the details are omitted here. The computer-readable storage medium may include a read-only memory (ROM), random access memory (RAM), a magnetic disk, or an optical disk, etc., without limitation herein.

[0163] The functional blocks shown in the above-described block diagram can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of the present application are programs or code segments that are used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or communication link via a data signal carried in a carrier wave. "Computer-readable medium" can include any medium capable of storing or transmitting information. Examples of computer-readable media include electronic circuits, semiconductor memory devices, ROMs, flash memories, erasable ROMs (EROMs), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency links, etc. The code segment can be downloaded via a computer network such as the Internet, an intranet, etc.

[0164] According to an embodiment of the present application, the computer-readable storage medium may be a non-transitory computer-readable storage medium.

[0165] It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, this application is not limited to the order of the above steps. In other words, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0166] Aspects of the present application have been described above with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer or other programmable data processing device to produce a machine so that these instructions executed via the processor of the computer or other programmable data processing device enable the implementation of the function / action specified in one or more boxes of the flowchart and / or block diagram. This processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor or a field programmable logic circuit. It is also understood that each box in the block diagram and / or the flowchart and the combination of the boxes in the block diagram and / or the flowchart can also be implemented by the dedicated hardware that performs the specified function or action, or can be implemented by the combination of dedicated hardware and computer instructions.

[0167] While the embodiments described above are not exhaustive, they do not limit the present application to the specific embodiments described. Clearly, numerous modifications and variations are possible based on the above description. These embodiments are selected and described in detail in this specification to better explain the principles and practical applications of the present application, thereby enabling those skilled in the art to better utilize the present application and its modifications. The present application is limited only by the claims and their full scope and equivalents.

Claims

1. A compensation method for a display panel, characterized in that: include: Setting multiple convolution kernels based on characteristics of multiple mura types; wherein the multiple convolution kernels correspond one-to-one to the multiple mura types, the numerical distribution characteristics of the convolution kernels are the same as the brightness distribution characteristics of the corresponding mura types, the convolution kernels include a matrix form, and the sum of all values ​​in the convolution kernels is 0; Using each of the convolution kernels to perform convolution operations on the initial compensation value matrix to obtain multiple extraction matrices; The display panel is compensated according to the initial compensation value matrix and the plurality of extraction matrices.

2. The method according to claim 1, characterized in that The number of rows and columns of the convolution kernel is positively correlated with the mura area of ​​the corresponding mura type.

3. The method according to claim 1, characterized in that The convolution operation is performed on the initial compensation value matrix using each convolution kernel to obtain multiple extraction matrices, including: Performing edge filling on the initial compensation value matrix; According to the convolution step size of 1, each convolution kernel is used to perform convolution operation on the initial compensation value matrix after edge filling to obtain multiple extraction matrices, and the number of rows and columns of each extraction matrix is ​​equal to the number of rows and columns of the initial compensation value matrix.

4. The method according to claim 1, wherein The edge filling of the initial compensation value matrix includes: The initial compensation value matrix is ​​edge-filled in a numerically symmetric manner.

5. The method according to claim 1, wherein The compensating the display panel according to the initial compensation value matrix and the plurality of extraction matrices includes: Correcting each of the extraction matrices according to a preset correction coefficient corresponding to each of the extraction matrices; The display panel is compensated according to the sum of the initial compensation value matrix and a plurality of modified extraction matrices.

6. The method according to claim 1, characterized in that The display panel includes sub-pixels of multiple colors, and the multiple initial compensation value matrices correspond one-to-one to the sub-pixels of multiple colors.

7. The method according to claim 1, characterized in that The initial compensation value matrix includes any one of an initial grayscale compensation value matrix, an initial data voltage compensation value matrix, and an initial brightness compensation value matrix.

8. A method for identifying mura of a display panel, characterized in that: include: Setting a convolution kernel according to a characteristic of a preset mura type; wherein a numerical distribution characteristic of the convolution kernel is the same as a brightness distribution characteristic of the preset mura type, the convolution kernel includes a matrix form, and the sum of all numerical values ​​in the convolution kernel is 0; Performing a convolution operation on the initial brightness value matrix of the display panel using the convolution kernel to obtain an extraction matrix; It is determined whether the display panel has the preset mura type according to the numerical distribution characteristics in the extraction matrix.

9. A compensation device for a display panel, characterized in that: include: A first setting module is configured to set a plurality of convolution kernels according to characteristics of a plurality of mura types; wherein the plurality of convolution kernels correspond one-to-one to the plurality of mura types, the numerical distribution characteristics of the convolution kernels are the same as the brightness distribution characteristics of the corresponding mura types, the convolution kernels include a matrix form, and the sum of all numerical values ​​in the convolution kernels is 0; A first operation module is used to perform convolution operation on the initial compensation value matrix using each convolution kernel to obtain multiple extraction matrices; A compensation determination module is configured to compensate the display panel according to the initial compensation value matrix and the plurality of extraction matrices.

10. A mura identification device for a display panel, characterized in that: include: A second setting module is configured to set a convolution kernel according to a characteristic of a preset mura type; wherein a numerical distribution characteristic of the convolution kernel is the same as a brightness distribution characteristic of the preset mura type, the convolution kernel includes a matrix form, and the sum of all numerical values ​​in the convolution kernel is 0; a second operation module, configured to perform a convolution operation on the initial brightness value matrix of the display panel using the convolution kernel to obtain an extraction matrix; The mura determination module is configured to determine whether the display panel has the preset mura type according to the value distribution in the extraction matrix.

11. An electronic device, characterized in that: include: A processor and a memory storing computer program instructions, wherein when the processor executes the computer program instructions, the display panel compensation method according to any one of claims 1 to 7 is implemented, or the display panel mura identification method according to claim 8 is implemented.

12. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the computer program implements the display panel compensation method according to any one of claims 1 to 7, or implements the display panel mura identification method according to claim 8.

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