Data processing method and device of display panel and computer readable storage medium

Abstract

Embodiments of the present application provide a data processing method and device of a display panel and a computer readable storage medium, the display panel comprises a plurality of partitions, each partition comprises at least one sub-pixel, the data processing method of the display panel comprises: obtaining compensation data of the plurality of partitions; based on a target vector compression algorithm, the compensation data of the plurality of partitions is compressed to obtain the compensation data of the plurality of partitions after compression. Embodiments of the present application can improve the compression accuracy of the compensation data and reduce the distortion degree of the compensation data after compression.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of display, and particularly relates to a data processing method and device of a display panel and a computer readable storage medium. BACKGROUND

[0002] In the production process of a display panel, uneven brightness may occur due to process, material, equipment and other factors, which is called Mura. At present, the mainstream Demura method is mainly an external optical compensation method, that is, the brightness data of the display panel is captured by a camera, compensation data is calculated by a Demura algorithm, the compensation data is written into a storage unit after data compression, so as to realize the brightness compensation of the display panel.

[0003] However, the brightness compensation effect of the display panel in the related art is poor. SUMMARY

[0004] The data processing method, device and computer readable storage medium of the display panel provided by the embodiments of the present application can improve the compression precision of compensation data and reduce the distortion degree of the compressed compensation data.

[0005] In a first aspect, the embodiments of the present application provide a data processing method of a display panel, the display panel comprising a plurality of partitions, each partition comprising at least one sub-pixel, the data processing method comprising: obtaining compensation data of the plurality of partitions; compressing the compensation data of the plurality of partitions based on a target vector compression algorithm to obtain compressed compensation data of the plurality of partitions.

[0006] According to the embodiments of the first aspect of the present application, before the step of compressing the compensation data of the plurality of partitions based on the target vector compression algorithm to obtain compressed compensation data of the plurality of partitions, the data processing method of the display panel can further comprise: for the compensation data of any one partition, compressing the compensation data of the partition based on the target vector compression algorithm of an initial clustering number adjustment coefficient to obtain compressed compensation data of the partition; decompressing the compressed compensation data of the partition to obtain decompressed compensation data of the partition; comparing the compensation data of the partition before compression with the decompressed compensation data of the partition, and determining a target clustering number adjustment coefficient according to a comparison result; and the step of compressing the compensation data of the plurality of partitions based on the target vector compression algorithm to obtain compressed compensation data of the plurality of partitions specifically comprises: compressing the compensation data of the partition based on the target vector compression algorithm of the target clustering number adjustment coefficient to obtain compressed compensation data of the partition.

[0007] Therefore, by flexibly adjusting the target cluster quantity adjustment coefficient corresponding to each partition, the compensation data of each partition can be compressed according to the appropriate cluster quantity adjustment coefficient, and the compensation data of each partition can have a large compression ratio under the condition of meeting the compression accuracy requirement, thereby greatly reducing the data quantity of each partition after compression.

[0008] According to any one of the foregoing embodiments of the first aspect of the present application, the step of comparing the compensation data of the partition before compression with the compensation data of the partition after decompression and determining the target cluster quantity adjustment coefficient according to the comparison result can specifically include: calculating the sum of absolute values of differences between the compensation data of the plurality of subpixels in the partition before compression and the compensation data of the plurality of subpixels in the partition after decompression; calculating a difference rate according to the sum and the number of subpixels in the partition; when the difference rate is greater than a preset threshold, increasing the cluster quantity adjustment coefficient until the difference rate is less than or equal to the preset threshold, to obtain the target cluster quantity adjustment coefficient; and / or when the difference rate is less than the preset threshold, decreasing the cluster quantity adjustment coefficient until the difference rate is greater than the preset threshold, and taking the cluster quantity adjustment coefficient after the last adjustment when the difference rate is less than or equal to the preset threshold as the target cluster quantity adjustment coefficient.

[0009] Therefore, when the difference rate is greater than the preset threshold, the cluster quantity adjustment coefficient is increased, and / or when the difference rate is less than the preset threshold, the cluster quantity adjustment coefficient is decreased, to obtain a relatively appropriate cluster quantity adjustment coefficient for each partition. By using the relatively appropriate cluster quantity adjustment coefficient for each partition to compress the compensation data, the compensation data of each partition can have a large compression ratio under the condition of meeting the compression accuracy requirement, thereby greatly reducing the data quantity of each partition after compression.

[0010] According to any one of the foregoing embodiments of the first aspect of the present application, the sum of absolute values of differences between the compensation data of the plurality of subpixels in the partition before compression and the compensation data of the plurality of subpixels in the partition after decompression is calculated according to the following expression:

[0011]

[0012] wherein D represents the sum, DataS(k) represents the compensation data of the kth subpixel in the partition before compression, DataD(k) represents the compensation data of the kth subpixel in the partition after decompression, n represents the number of subpixels in the partition, abs represents the absolute value operation, k and n are positive integers, and 1≤k≤n.

[0013] Therefore, by using the above expression, the sum of absolute values of differences between the compensation data of the plurality of subpixels in the partition before compression and the compensation data of the plurality of subpixels in the partition after decompression can be quickly and accurately obtained.

[0014] According to any one of the foregoing embodiments of the first aspect of the present application, the difference rate is calculated according to the following expression:

[0015] ratio = 100% * D / n

[0016] wherein ratio represents the difference rate, and n represents the number of subpixels in the partition, n being a positive integer.

[0017] In this way, the difference rate obtained by the above expression can objectively and accurately reflect the difference between the compensation data of the partition before compression and the compensation data of the partition after decompression.

[0018] According to any one of the foregoing embodiments of the first aspect of the present application, the adjustment step of the cluster quantity adjustment coefficient comprises 1.

[0019] In this way, when the adjustment step of the cluster quantity adjustment coefficient is 1, for example, it can be avoided that the final target cluster quantity adjustment coefficient is inaccurate due to the adjustment step of the cluster quantity adjustment coefficient being set too large, and for example, it can be avoided that too much time is spent in determining the target cluster quantity adjustment coefficient due to the adjustment step of the cluster quantity adjustment coefficient being set too small.

[0020] According to any one of the foregoing embodiments of the first aspect of the present application, the compensation data of the plurality of partitions comprises first compensation data of the plurality of partitions corresponding to a first target gray scale and second compensation data of the plurality of partitions corresponding to a second target gray scale, the first target gray scale being different from the second target gray scale; the preset threshold corresponding to the first target gray scale is different from the preset threshold corresponding to the second target gray scale; and / or the difference rate is determined according to the cumulative sum, the number of subpixels in the partition, and the adjustment coefficient, the adjustment coefficient corresponding to the first target gray scale being different from the adjustment coefficient corresponding to the second target gray scale.

[0021] In this way, since the preset threshold and / or the adjustment coefficient corresponding to different gray scales are different, the target cluster quantity adjustment coefficients obtained at different gray scales can be different. In this way, the compensation data of different gray scales can be compressed based on different target cluster quantity adjustment coefficients, so that the compensation data of different gray scales has a larger compression ratio under the condition of meeting the compression accuracy requirement, and the amount of data after compression is greatly reduced.

[0022] According to any one of the foregoing embodiments of the first aspect of the present application, the difference rate is calculated according to the following expression:

[0023] ratio = 100% * D / n * p

[0024] wherein ratio represents the difference rate, n represents the number of subpixels in the partition, p is the adjustment coefficient, p ≥ 1, and n is a positive integer.

[0025] According to any one of the foregoing embodiments of the first aspect of the application, the first target gray scale is smaller than the second target gray scale; the preset threshold corresponding to the first target gray scale is smaller than the preset threshold corresponding to the second target gray scale; and / or the adjustment coefficient corresponding to the first target gray scale is smaller than the adjustment coefficient corresponding to the second target gray scale.

[0026] In this way, when the gray scale is high, the judgment criterion of the difference rate can be appropriately relaxed, so as to obtain a smaller cluster quantity adjustment coefficient, so that the compensation data is compressed as much as possible under the condition of meeting the compression accuracy requirement, and the amount of compressed data is greatly reduced.

[0027] According to any one of the foregoing embodiments of the first aspect of the application, the step of compressing the compensation data of the partition based on the target vector compression algorithm of the target cluster quantity adjustment coefficient can specifically include: for any one partition, dividing the compensation data of the plurality of sub-pixels in the target gray scale in the partition into N intervals, and determining the center value of each interval according to the compensation data of the sub-pixels in the target gray scale contained in each interval, the target gray scale being any one gray scale binding point, and N = 2 K , K is the target cluster quantity adjustment coefficient, and K and N are positive integers; for any one sub-pixel in the partition, generating an index value corresponding to the sub-pixel according to the interval to which the compensation data of the sub-pixel belongs; the compressed compensation data of the partition includes the center value of each interval and the index value corresponding to each sub-pixel in the partition; and the data processing method of the display panel further includes: for any one partition, storing the center value of each interval in the partition and the index value corresponding to each sub-pixel in the partition into a storage unit.

[0028] In this way, the compensation data is compressed by applying the target vector quantization algorithm, on the one hand, the compensation data of all the sub-pixels in each interval at the target gray scale is replaced by the same center value, which can greatly reduce the data amount and save storage space; on the other hand, the compensation data can be classified and compressed according to the data size, the compression accuracy of the compensation data is improved, the original data characteristics are better preserved, the distortion degree of the compressed compensation data is reduced, and the Demura compensation effect is improved.

[0029] According to any one of the foregoing embodiments of the first aspect of the present application, before the step of storing the center value of each interval in the partition and the subscript value corresponding to each sub-pixel in the partition into the storage unit, the data processing method of the display panel can further include: limiting the number of bits of the center value to a second number of bits, the second number of bits being less than the first number of bits; and / or limiting the number of bits of the subscript value to a third number of bits, the third number of bits being less than the first number of bits; and the step of storing the center value of each interval in the partition and the subscript value corresponding to each sub-pixel in the partition into the storage unit specifically includes: storing the center value of each interval in the partition after limiting the number of bits and / or the subscript value corresponding to each sub-pixel in the partition after limiting the number of bits into the storage unit.

[0030] In this way, by limiting the number of bits of the center value and / or the subscript value, the data range of the center value and / or the subscript value can be further reduced, and the data amount of the center value and / or the subscript value can also be reduced, thereby further reducing the data amount of the center value and further reducing the storage cost of the storage unit.

[0031] According to any one of the foregoing embodiments of the first aspect of the present application, the step of decompressing the compressed compensation data of the partitions to obtain decompressed compensation data of the partitions specifically can include: for any one sub-pixel in the partition, determining the center value corresponding to the sub-pixel at the target gray scale according to the correspondence between the subscript value and the center value at the target gray scale and the subscript value of the sub-pixel; and taking the center value corresponding to the sub-pixel as the compensation data of the sub-pixel at the target gray scale.

[0032] According to any one of the foregoing embodiments of the first aspect of the present application, the step of compressing the compensation data of the plurality of partitions based on the target vector compression algorithm to obtain compressed compensation data of the plurality of partitions specifically can include: for any one partition, determining the background data corresponding to the partition according to the gray scale displayed by the partition; removing the background data from the compensation data of the partition to obtain compensation data of the partition after removing the background data; and compressing the compensation data of the partition after removing the background data based on the target vector compression algorithm to obtain the compressed compensation data of the partition.

[0033] In this way, by removing the background data from the compensation data of the partition to obtain the compensation data of the partition after removing the background data, the data amount of the compensation data can be further reduced.

[0034] According to any one of the foregoing embodiments of the first aspect of the application, before the step of compressing the compensation data of each partition based on the target vector compression algorithm to obtain the compressed compensation data of each partition, the data processing method of the display panel can further include: performing mean compression on the compensation data of each partition based on a block compression algorithm to obtain mean compressed compensation data of each partition; and the step of compressing the compensation data of each partition based on the target vector compression algorithm to obtain the compressed compensation data of each partition can specifically include: compressing the mean compressed compensation data of each partition based on the target vector compression algorithm to obtain the compressed compensation data of each partition.

[0035] In this way, the compensation data of each partition is first compressed based on the block compression algorithm, which can further reduce the data amount of the compensation data, save storage space, and reduce storage costs.

[0036] According to any one of the foregoing embodiments of the first aspect of the application, the target vector compression algorithm can include an LBG algorithm.

[0037] In this way, the compensation data of the plurality of partitions is compressed using the LBG algorithm, which can classify and compress the compensation data of each partition according to the data size of the compensation data of each partition, improve the compression accuracy of the compensation data, better preserve the original data characteristics, reduce the distortion of the compressed compensation data, and further improve the Demura compensation effect.

[0038] According to any one of the foregoing embodiments of the first aspect of the application, the target cluster quantity adjustment coefficients of at least some of the partitions are different.

[0039] In this way, for the compensation data of different partitions, the target cluster quantity adjustment coefficients of each partition are flexibly adjusted, so that the compensation data of each partition is compressed according to the appropriate target cluster quantity adjustment coefficient of each partition, the compensation data of each partition has a large compression ratio under the condition of meeting the compression accuracy requirement, and the data amount of each partition after compression is greatly reduced.

[0040] In a second aspect, the embodiments of the application provide a data processing apparatus of a display panel. The display panel includes a plurality of partitions, and each partition includes at least one sub-pixel. The data processing apparatus of the display panel includes: an acquisition module configured to acquire compensation data of the plurality of partitions; and a first compression module configured to compress the compensation data of the plurality of partitions based on a target vector compression algorithm to obtain compressed compensation data of the plurality of partitions.

[0041] In a third aspect, the embodiments of the application provide a computer-readable storage medium. The computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the steps of the data processing method provided in the first aspect are implemented.

[0042] The data processing method, device and computer readable storage medium of the display panel provided by the embodiments of the present application obtain compensation data of multiple partitions in the display panel; the compensation data of the multiple partitions is compressed based on a target vector compression algorithm to obtain compressed compensation data of the multiple partitions. The embodiments of the present application apply the target vector quantization algorithm to compress the compensation data of the multiple partitions, can classify and compress the compensation data of the multiple partitions according to the data size of the compensation data of each partition, improve the compression precision of the compensation data, better retain the original data characteristics, reduce the distortion degree of the compressed compensation data, and further improve the Demura compensation effect. BRIEF DESCRIPTION OF DRAWINGS

[0043] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required to be used in the embodiments of the present application will be briefly introduced below. Those skilled in the art can obtain other drawings according to these drawings without creating any creative labor.

[0044] Figure 1 A flowchart of the data processing method of the display panel provided by the embodiments of the present application is shown in FIG. 1.

[0045] Figure 2 Another flowchart of the data processing method of the display panel provided by the embodiments of the present application is shown in FIG. 2.

[0046] Figure 3 A flowchart of S203 in the data processing method of the display panel provided by the embodiments of the present application is shown in FIG. 3.

[0047] Figure 4 Another flowchart of the data processing method of the display panel provided by the embodiments of the present application is shown in FIG. 4.

[0048] Figure 5 Another flowchart of the data processing method of the display panel provided by the embodiments of the present application is shown in FIG. 5.

[0049] Figure 6 Another flowchart of S202 in the data processing method of the display panel provided by the embodiments of the present application is shown in FIG. 6.

[0050] Figure 7 Another flowchart of S102 in the data processing method of the display panel provided by the embodiments of the present application is shown in FIG. 7.

[0051] Figure 8 Another flowchart of the data processing method of the display panel provided by the embodiments of the present application is shown in FIG. 8.

[0052] Figure 9A structural schematic diagram of a data processing apparatus of a display panel provided by an embodiment of the present application is shown.

[0053] Figure 10 A hardware structural schematic diagram of an electronic device provided by an embodiment of the present application is shown. DETAILED DESCRIPTION

[0054] The features and exemplary embodiments of various aspects of the present application will be described in detail below with reference to the drawings. To make the purpose, technical solutions and advantages of the present application more clear, the present application will be further described in detail below with reference to the drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, but not to limit the present application. The present application can be implemented without some of the specific details by those skilled in the art. The following description of the embodiments is only to provide a better understanding of the present application by showing examples of the present application.

[0055] It should be noted that, in this document, the relationship terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply that there is any such actual relationship or order between the entities or operations. Moreover, the terms “include”, “contain” or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or device. Without more limitations, the elements defined by the statement “include” do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0056] It should be understood that the term “and / or” used herein is only to describe the association relationship of the associated objects, which means that there can be three relationships, for example, A and / or B can mean that there are three cases of A alone, A and B together, and B alone. In addition, the character “ / ” herein generally represents that the front and rear associated objects have an “or” relationship.

[0057] Various modifications and changes can be made to the present application without departing from the spirit or scope of the present application, which will be apparent to those skilled in the art. Therefore, the present application is intended to cover the modifications and changes of the present application falling within the scope of the corresponding claims (claimed technical solutions) and their equivalents. It should be noted that the embodiments provided by the embodiments of the present application can be combined with each other without contradiction.

[0058] Before the technical solutions provided by the embodiments of the present application are described, in order to facilitate the understanding of the embodiments of the present application, the present application first specifically describes the problems existing in the related art:

[0059] The display panel may appear uneven brightness due to process, material, equipment and other factors during production, which is called Mura. At present, the mainstream Demura method is mainly an external optical compensation method, that is, the brightness data of the display panel is captured by a camera, the compensation data is calculated by a Demura algorithm, and the compensation data is written into a storage unit, so as to realize the brightness compensation of the display panel.

[0060] The storage unit includes but is not limited to a static random access memory (SRAM). The storage capacity of the current storage unit (such as Demura SRAM) is about 16M, but due to the demand for the number of captured gray scales and the depth of compensation data, the amount of data written into the storage unit is large. Therefore, the compensation data needs to be compressed to meet the hardware resource demand.

[0061] The present inventors have found through long-term research that the number of captured gray scales and the accuracy of compensation data jointly affect the memory size occupied by the data and the compensation effect. When the memory size occupied is certain, the more the number of captured gray scales, the more accurate the calculation, but the corresponding compensation data depth (i.e., data range) is lower, and after compensation, phenomena such as sandiness, under-compensation or over-compensation are likely to occur. On the contrary, if the number of captured gray scales is reduced and the compensation data depth is increased, the captured gray scale compensation effect is good, but there is a problem of poor interpolation calculation gray scale compensation effect. Therefore, data compression plays a key role in this process, and it is necessary to retain sufficient captured gray scales and try to retain the compensation data depth to achieve the best compensation effect.

[0062] However, the present inventors have found through long-term research that the compression method (such as the mean compression method) currently used may cause the compressed compensation data to be distorted greatly after compression. If the Demura compensation is performed using the compressed compensation data with large distortion, the Demura compensation effect will be poor.

[0063] In view of the above research findings of the inventors, the embodiments of the present application provide a display panel data processing method and device and a computer readable storage medium, which can solve the technical problem that the compensation data is greatly distorted after data compression in the related art, resulting in poor Demura compensation effect.

[0064] The technical concept of the embodiments of the present application is that, for compensation data of multiple partitions in a display panel, the compensation data of the multiple partitions is compressed based on a target vector compression algorithm to obtain compressed compensation data of the multiple partitions. The target vector quantization algorithm can classify and compress the compensation data of each partition according to the data size of the compensation data of each partition, improve the compression precision of the compensation data, better retain the original data characteristics, reduce the distortion of the compressed compensation data, and thus improve the Demura compensation effect.

[0065] First, the data processing method of the display panel provided by the embodiments of the present application will be introduced.

[0066] In the embodiments of the present application, the display panel can include multiple partitions, and each partition can include at least one sub-pixel. It should be noted that the number of partitions in the display panel and the number of sub-pixels in the partitions can be flexibly adjusted according to actual conditions, and the embodiments of the present application do not limit this, for example, in some examples, each partition can include 10*10 sub-pixels; each partition can also include 40*40 sub-pixels; preferably, the number of sub-pixels in each partition can also be between the two, i.e., (10-40)*(10-40) sub-pixels. In addition, the number of sub-pixels in different partitions can be the same or different, and the embodiments of the present application do not limit this.

[0067] Figure 1 A flowchart of the data processing method of the display panel provided by the embodiments of the present application is shown in FIG. 1. Figure 1 As shown in FIG. 1, the data processing method of the display panel can include the following steps S101 and S102.

[0068] S101, obtaining compensation data of multiple partitions.

[0069] The compensation data can be compensation data obtained by performing external optical compensation on the display panel, i.e., Demura compensation data, for improving the mura phenomenon of the display panel. In some examples, the compensation data of each partition can include a gray scale compensation value of a sub-pixel in each partition, for example, H2 = H1 ± ΔH, where ΔH represents a gray scale compensation value of any i-th sub-pixel, H1 represents a gray scale before Demura compensation of the i-th sub-pixel, H2 represents a gray scale after Demura compensation of the i-th sub-pixel, and i is a positive integer. In other examples, the compensation data of each partition can include a gray scale adjustment coefficient of a sub-pixel in each partition, for example, H2 = a(H1) + b*H1, where a and b represent a gray scale adjustment coefficient of any i-th sub-pixel, H1 represents a gray scale before Demura compensation of the i-th sub-pixel, H2 represents a gray scale after Demura compensation of the i-th sub-pixel, and i is a positive integer. 2 ​

[0070] According to some embodiments of the present application, in S101, compensation data of a plurality of partitions at at least one different gray scale binding point can be acquired. The compensation data of the same partition at different gray scale binding points can be different. For example, at least one gray scale binding point can be set, and the size and number of the gray scale binding points are not limited in the embodiments of the present application. For example, in some examples, the set gray scale binding points can include 16 gray scales, 64 gray scales and 192 gray scales. For another example, in some examples, the set gray scale binding points can include 16 gray scales, 64 gray scales, 128 gray scales and 192 gray scales, etc.

[0071] In S102, the compensation data of the plurality of partitions can be compressed based on a target vector compression algorithm to obtain compressed compensation data of the plurality of partitions.

[0072] The target vector quantization algorithm includes but is not limited to LBG algorithm. The LBG algorithm is a vector quantization (VQ) design algorithm based on a training sequence. First, the number of center points is set, then the iteration is continuously looped, the set threshold is used as the iteration termination condition, and finally the value of the center point is obtained. Its advantage is that the data size can be used to classify the values, for example, the values with smaller values are classified as A, the values with medium values are classified as B, and the values with larger values are classified as C. The above three classifications are only illustrative. The larger the number of center points is set, the more the classification is, and the higher the compression accuracy is. Compared with the usual scalar quantization, the distortion obtained by using vector quantization is lower.

[0073] In S102, the compensation data of the plurality of partitions can be compressed based on a target vector compression algorithm to obtain compressed compensation data of the plurality of partitions.

[0074] The data processing method of the display panel according to the embodiments of the present application acquires compensation data of a plurality of partitions in the display panel; and compresses the compensation data of the plurality of partitions based on a target vector compression algorithm to obtain compressed compensation data of the plurality of partitions. The embodiments of the present application apply the target vector quantization algorithm to compress the compensation data of the plurality of partitions, which can classify and compress the compensation data of each partition according to the data size of the compensation data of each partition, improve the compression accuracy of the compensation data, better retain the original data characteristics, reduce the distortion of the compressed compensation data, and further improve the Demura compensation effect.

[0075] The inventors of the present application further realize that the compression accuracy and compression ratio of the target vector compression algorithm are affected by the cluster quantity adjustment coefficient (or the number of splits) K. The greater the cluster quantity adjustment coefficient K, the higher the compression accuracy (i.e., the smaller the compression loss rate), and the smaller the compression ratio, and the greater the amount of compressed data. The smaller the cluster quantity adjustment coefficient K, the lower the compression accuracy (i.e., the greater the compression loss rate), and the greater the compression ratio, and the smaller the amount of compressed data. Therefore, a balance needs to be struck between the compression accuracy and the compression ratio, so that the compensation data can meet the compression accuracy requirement while having a large compression ratio to greatly reduce the amount of compressed data.

[0076] Therefore, for the compensation data of different partitions, the cluster quantity adjustment coefficient corresponding to each partition can be determined respectively, so that the compensation data of each partition can meet the compression accuracy requirement while greatly reducing the amount of compressed data.

[0077] Figure 2 Another flowchart of the data processing method of the display panel provided by the embodiments of the present application is shown in FIG. 2. As shown in FIG. 2, according to some embodiments of the present application, before the step of S102, compressing the compensation data of the plurality of partitions based on the target vector compression algorithm to obtain the compensation data of the plurality of partitions after compression, the data processing method of the display panel can further include S201 to S203. Figure 2

[0078] S201, for the compensation data of any one partition, compressing the compensation data of the partition based on the target vector compression algorithm with the initial cluster quantity adjustment coefficient to obtain the compensation data of the partition after compression.

[0079] The initial cluster quantity adjustment coefficient can be preset, i.e., the initial value of the cluster quantity adjustment coefficient. The size of the initial cluster quantity adjustment coefficient can be flexibly adjusted according to actual conditions, which is not limited by the embodiments of the present application. For example, in some examples, the initial cluster quantity adjustment coefficient can be 4, and of course the initial cluster quantity adjustment coefficient can also be other numerical values.

[0080] For the compensation data of any one partition, the compensation data of the partition can be first compressed based on the target vector compression algorithm with the initial cluster quantity adjustment coefficient to obtain the compensation data of the partition after compression.

[0081] S202, decompressing the compensation data of the partition after compression to obtain the compensation data of the partition after decompression.

[0082] In S202, the compensation data of the partition after compression can be decompressed, i.e., restored, to obtain the compensation data of the partition after decompression.

[0083] ​S203, compare the compensation data of the partition before compression with the compensation data of the partition after decompression, and determine the target cluster quantity adjustment coefficient according to the comparison result.

[0084] In S203, the compensation data of the partition before compression can be compared with the compensation data of the partition after decompression. For example, if the difference between the two is large, it means that the current compression accuracy does not meet the requirements, and the cluster quantity adjustment coefficient needs to be adjusted; if the difference between the two is small, it means that the current compression accuracy meets the requirements, and the cluster quantity adjustment coefficient can not be adjusted. Therefore, according to the comparison result of the compensation data of the partition before compression and the compensation data of the partition after decompression, the target cluster quantity adjustment coefficient used by the partition can be determined.

[0085] Correspondingly, S102, based on the target vector compression algorithm, the compensation data of the plurality of partitions is compressed to obtain the compensation data of the plurality of partitions after compression. Specifically, the step can include the following steps:

[0086] Based on the target cluster quantity adjustment coefficient, the target vector compression algorithm is used to compress the compensation data of the partition to obtain the compensation data of the partition after compression.

[0087] Specifically, after obtaining the target cluster quantity adjustment coefficient corresponding to each partition, for any ith partition, i is a positive integer, the cluster quantity adjustment coefficient of the target vector compression algorithm can be adjusted to be equal to the target cluster quantity adjustment coefficient corresponding to the ith partition, and then the compensation data of the ith partition is compressed to obtain the compensation data of the ith partition after compression.

[0088] In this way, for the compensation data of different partitions, by flexibly adjusting the target cluster quantity adjustment coefficient corresponding to each partition, the compensation data of each partition can be compressed according to the appropriate cluster quantity adjustment coefficient, so that the compensation data of each partition can have a large compression ratio under the condition of meeting the compression accuracy requirement, and the data amount of each partition after compression can be greatly reduced.

[0089] Figure 3 A flowchart of S203 in the data processing method of the display panel provided by the embodiments of the present application is shown in FIG. 3. Figure 3 As shown in FIG. 3, according to some embodiments of the present application, the step of S203, comparing the compensation data of the partition before compression with the compensation data of the partition after decompression, and determining the target cluster quantity adjustment coefficient according to the comparison result, can specifically include the following steps S301 and S302, and can also include at least one of S303 and S304.

[0090] S301, calculate the sum of absolute values of differences between the compensation data of the plurality of sub-pixels before compression and the compensation data of the plurality of sub-pixels after decompression in the partition.

[0091] A partition can include a plurality of sub-pixels. Accordingly, the compensation data before compression of a partition can include the compensation data of the plurality of sub-pixels in the partition before compression, and the compensation data after decompression of a partition can include the compensation data of the plurality of sub-pixels in the partition after decompression.

[0092] Taking a partition including N1 sub-pixels as an example, N1 is an integer greater than 1, in S301, for any partition, the absolute value of the difference between the compensation data of the first sub-pixel in the partition before compression and the compensation data of the first sub-pixel in the partition after decompression can be calculated, the absolute value of the difference between the compensation data of the second sub-pixel in the partition before compression and the compensation data of the second sub-pixel in the partition after decompression can be calculated, and so on, the absolute value of the difference between the compensation data of the N1th sub-pixel in the partition before compression and the compensation data of the N1th sub-pixel in the partition after decompression can be calculated. Then, the absolute values of the differences corresponding to each sub-pixel are added to obtain the sum of absolute values of differences between the compensation data of the plurality of sub-pixels in the partition before compression and the compensation data of the plurality of sub-pixels in the partition after decompression (hereinafter referred to as "sum of absolute values of differences").

[0093] S302, calculate the difference rate according to the sum of absolute values of differences and the number of sub-pixels in the partition.

[0094] Since the sum of absolute values of differences obtained by S301 will change when the number of sub-pixels in the partition changes. Therefore, in order to more objectively and accurately reflect the difference between the compensation data of the partition before compression and the compensation data of the partition after decompression, the difference rate can be obtained according to the sum of absolute values of differences obtained by S301 and the number of sub-pixels in the partition. The difference rate can objectively and accurately reflect the difference between the compensation data of the partition before compression and the compensation data of the partition after decompression.

[0095] S303, when the difference rate is greater than the preset threshold, increase the clustering number adjustment coefficient until the difference rate is less than or equal to the preset threshold, and obtain the target clustering number adjustment coefficient.

[0096] As mentioned earlier, the larger the clustering number adjustment coefficient, the higher the compression accuracy. When the difference rate is greater than the preset threshold, it means that the currently adopted clustering number adjustment coefficient is small, resulting in compression accuracy that does not meet the requirements. Therefore, when the difference rate is greater than the preset threshold, the clustering number adjustment coefficient can be increased until the difference rate is less than or equal to the preset threshold, thereby obtaining the target clustering number adjustment coefficient.

[0097] For example, when the difference rate is greater than the preset threshold, the cluster quantity adjustment coefficient can be increased by a preset adjustment step, and then the initial cluster quantity adjustment coefficient is updated to the increased cluster quantity adjustment coefficient. For example, the initial cluster quantity adjustment coefficient is 4, and the increased cluster quantity adjustment coefficient is 5, and then the initial cluster quantity adjustment coefficient is changed from 4 to 5. Then, return to steps S201 to S203 until the difference rate is less than or equal to the preset threshold. Finally, the cluster quantity adjustment coefficient corresponding to the difference rate less than or equal to the preset threshold is taken as the target cluster quantity adjustment coefficient.

[0098] The size of the preset threshold can be flexibly adjusted according to actual conditions, and the embodiments of the present application are not limited.

[0099] S304, when the difference rate is less than the preset threshold, the cluster quantity adjustment coefficient is reduced until the difference rate is greater than the preset threshold, and the cluster quantity adjustment coefficient adjusted last time when the difference rate is less than or equal to the preset threshold is taken as the target cluster quantity adjustment coefficient.

[0100] The inventors of the present application have further found through long-term research that in some cases, for example, based on the cluster quantity adjustment coefficient k=4 to compress the compensation data of the partition, although the compression accuracy requirement can be met, there is a "waste" situation, that is, there is no use of the subscript value (the subscript value in the following text), which leads to the data volume of the compressed compensation data still being too large.

[0101] Therefore, in S304, when the difference rate is less than the preset threshold, the cluster quantity adjustment coefficient can be reduced until the difference rate is greater than the preset threshold, and the cluster quantity adjustment coefficient adjusted last time when the difference rate is less than or equal to the preset threshold is taken as the target cluster quantity adjustment coefficient.

[0102] For example, when the cluster quantity adjustment coefficient is 4, the difference rate is less than the preset threshold. When the cluster quantity adjustment coefficient is reduced to 3, the difference rate is still less than the preset threshold. However, when the cluster quantity adjustment coefficient is reduced to 2, the difference rate is greater than the preset threshold. Then, the cluster quantity adjustment coefficient adjusted last time when the difference rate is less than or equal to the preset threshold, such as 3, is taken as the target cluster quantity adjustment coefficient. It should be noted that the above 2, 3 and 4 are only examples and do not constitute a limitation to the present application.

[0103] Thus, when the difference rate is greater than the preset threshold, the cluster quantity adjustment coefficient is increased, and / or when the difference rate is less than the preset threshold, the cluster quantity adjustment coefficient is decreased, so that a relatively appropriate cluster quantity adjustment coefficient of each partition can be obtained. By using the relatively appropriate cluster quantity adjustment coefficient of each partition to compress the compensation data, the compensation data of each partition can have a relatively large compression ratio and a relatively large reduction in the amount of data after compression, while meeting the compression accuracy requirement.

[0104] In some specific embodiments, the sum of absolute values of the difference between the compensation data of the plurality of sub-pixels before compression and the compensation data of the plurality of sub-pixels after decompression in the partition can be calculated according to the following expression:

[0105]

[0106] wherein D represents the sum, DataS(k) represents the compensation data of the kth sub-pixel in the partition before compression, DataD(k) represents the compensation data of the kth sub-pixel in the partition after decompression, n represents the number of sub-pixels in the partition, abs represents the absolute value operation, and k and n are positive integers, 1≤k≤n.

[0107] Thus, the sum of absolute values of the difference between the compensation data of the plurality of sub-pixels before compression and the compensation data of the plurality of sub-pixels after decompression in the partition can be quickly and accurately obtained by using the above expression (1).

[0108] In some specific embodiments, the difference rate can be calculated according to the following expression:

[0109] ratio=100%*D / n (2)

[0110] wherein ratio represents the difference rate, and n represents the number of sub-pixels in the partition, n being a positive integer.

[0111] For example, in some examples, one partition can include 20*20 sub-pixels, i.e., 400 sub-pixels, and accordingly, n can be equal to 400.

[0112] Thus, the difference rate obtained by using the above expression (2) can objectively and accurately reflect the difference between the compensation data of the partition before compression and the compensation data of the partition after decompression.

[0113] In some embodiments, the adjustment step of the cluster quantity adjustment coefficient can be 1. That is, the step of increasing the cluster quantity adjustment coefficient and / or the step of decreasing the cluster quantity adjustment coefficient can be 1. When the adjustment step of the cluster quantity adjustment coefficient is 1, the final adopted target cluster quantity adjustment coefficient can be inaccurate due to a large adjustment step of the cluster quantity adjustment coefficient, and the time spent in determining the target cluster quantity adjustment coefficient can be too long due to a small adjustment step of the cluster quantity adjustment coefficient.

[0114] The inventors of the present application further realize that the sensitivity of the human eye to high gray scales and low gray scales is different. For example, at low gray scales, the human eye can be very sensitive to a difference of more than 10%, such as a change of ±1 gray scale. However, at high gray scales, the screen is brighter, and at this time, the human eye is not sensitive, and the human eye can not be able to find a difference of more than 10%, such as a change of ±3 gray scales. Therefore, for compensation data of different gray scales, different difference judgment criteria can be used, such as different preset thresholds at different gray scales.

[0115] Specifically, according to some embodiments of the present application, the compensation data of the plurality of partitions can include first compensation data of the plurality of partitions at a first target gray scale and second compensation data of the plurality of partitions at a second target gray scale, the first target gray scale being different from the second target gray scale. The first target gray scale and the second target gray scale can be any gray scale, which is not limited in the embodiments of the present application. The preset threshold corresponding to the first target gray scale is different from the preset threshold corresponding to the second target gray scale.

[0116] For example, the preset threshold corresponding to the first target gray scale can be 10%. For the first compensation data, when the difference ratio ratio is greater than 10%, the cluster quantity adjustment coefficient can be increased, and when the difference ratio ratio is less than 10%, the cluster quantity adjustment coefficient can be decreased. For example, the preset threshold corresponding to the second target gray scale can be 20%. For the second compensation data, when the difference ratio ratio is greater than 20%, the cluster quantity adjustment coefficient can be increased, and when the difference ratio ratio is less than 20%, the cluster quantity adjustment coefficient can be decreased.

[0117] In this way, since the preset thresholds corresponding to different gray scales are different, the target cluster quantity adjustment coefficients obtained at different gray scales can be different. In this way, the compensation data of different gray scales can be compressed based on different target cluster quantity adjustment coefficients, so that the compensation data of different gray scales has a large compression ratio under the condition of meeting the compression accuracy requirement, and the amount of compressed data is greatly reduced.

[0118] According to some embodiments of the present application, the adjustment factor related to the gray scale can also be used to adjust the difference ratio, for example, so that different gray scales calculate different difference ratios.

[0119] Specifically, the difference ratio can be determined according to the cumulative, the number of subpixels in the partition, and the adjustment factor. The adjustment factor corresponding to the first target gray scale can be different from the adjustment factor corresponding to the second target gray scale.

[0120] For example, in some specific embodiments, the difference ratio can be calculated according to the following expression:

[0121] ratio = 100% * D / n * p (3)

[0122] Wherein, ratio represents the difference ratio, n represents the number of subpixels in the partition, and p is the adjustment factor, p≥1, and n is a positive integer.

[0123] As can be seen from the above expression (3), the difference ratio ratio is also affected by the adjustment factor p, for example, the larger the adjustment factor p, the smaller the difference ratio ratio; the smaller the adjustment factor p, the larger the difference ratio ratio. The adjustment factor p can be related to the gray scale, for example, the adjustment factor corresponding to the first target gray scale can be different from the adjustment factor corresponding to the second target gray scale.

[0124] It should be noted that when the adjustment factor corresponding to the first target gray scale is different from the adjustment factor corresponding to the second target gray scale, the preset threshold corresponding to the first target gray scale can be the same as the preset threshold corresponding to the second target gray scale, or different, and the embodiments of the present application do not limit this.

[0125] Therefore, because the adjustment factors corresponding to different gray scales are different, the target cluster number adjustment factors obtained under different gray scales can be different. In this way, the compensation data of different gray scales can be compressed based on different target cluster number adjustment factors, so that the compensation data of different gray scales has a larger compression ratio under the condition of meeting the compression precision requirement, and the amount of compressed data is greatly reduced.

[0126] In some specific embodiments, the first target gray scale can be smaller than the second target gray scale. For example, the first target gray scale is a lower gray scale, and the second target gray scale is a higher gray scale.

[0127] Correspondingly, the preset threshold corresponding to the first target gray scale can be smaller than the preset threshold corresponding to the second target gray scale.

[0128] For example, the preset threshold corresponding to the first target gray scale can be 10%. For the first compensation data, when the difference ratio ratio is greater than 10%, the cluster number adjustment coefficient can be increased, and when the difference ratio ratio is less than 10%, the cluster number adjustment coefficient can be decreased. For example, the preset threshold corresponding to the second target gray scale can be 20%. For the second compensation data, when the difference ratio ratio is greater than 20%, the cluster number adjustment coefficient can be increased, and when the difference ratio ratio is less than 20%, the cluster number adjustment coefficient can be decreased.

[0129] That is, when the gray scale is high, the difference ratio ratio can be appropriately relaxed, so that a smaller cluster number adjustment coefficient is obtained, so that the compensation data is compressed as much as possible under the condition of meeting the compression accuracy requirement, and the compressed data amount is greatly reduced.

[0130] In some embodiments, when the first target gray scale is less than the second target gray scale, the adjustment coefficient corresponding to the first target gray scale can be less than the adjustment coefficient corresponding to the second target gray scale.

[0131] As described above, the larger the adjustment coefficient p is, the smaller the difference ratio ratio is; the smaller the adjustment coefficient p is, the larger the difference ratio ratio is. Therefore, when the gray scale is high, the corresponding adjustment coefficient p is large, the difference ratio ratio can be reduced, and the cluster number adjustment coefficient is small, so that the compression accuracy requirement can be met.

[0132] For example, taking the adjustment coefficient p=1 corresponding to the first target gray scale and the adjustment coefficient p=2 corresponding to the second target gray scale as an example, according to the above expression (3), when p=1, ratio=100%*D / n, and when 100%*D / n is greater than the preset threshold, the cluster number adjustment coefficient needs to be increased. When p=2, ratio=100%*D / n*2, and only when the cumulative sum D is increased to 2D, 100%*2*D / n*2 will be equal to 100%*D / n, that is, it is equivalent to when the cumulative sum D is increased to 2D, the cluster number adjustment coefficient needs to be increased. In this way, a smaller cluster number adjustment coefficient can be used, so that the compensation data is compressed as much as possible under the condition of meeting the compression accuracy requirement, and the compressed data amount is greatly reduced.

[0133] The compression process of the target vector quantization algorithm will be described in detail below.

[0134] Figure 4 Another flowchart of the data processing method of the display panel provided by the embodiments of the present application is shown in FIG. 6. Figure 4As shown, according to some embodiments of the present application, the target vector compression algorithm based on the target cluster quantity adjustment coefficient is optionally used to compress the compensation data of the partition to obtain the compressed compensation data of the partition, which can specifically include the following steps S401 and S402.

[0135] S401, for any one partition, the compensation data of the plurality of sub-pixels in the target gray scale is divided into N intervals, and the center value of each interval is determined according to the compensation data of the sub-pixels in the target gray scale contained in each interval.

[0136] Wherein, the target gray scale is any one gray scale binding point, for example, the target gray scale can be 16 gray scale, 64 gray scale, 192 gray scale or other gray scale. N = 2 K , K is the target cluster quantity adjustment coefficient, K and N are positive integers. It can be seen that the number of intervals or the number of center values is affected by the target cluster quantity adjustment coefficient K, for example, when the target cluster quantity adjustment coefficient K = 4, N = 2 4 = 16, that is, the compensation data of the plurality of sub-pixels in the target gray scale in a partition is divided into 16 intervals to obtain 16 center values.

[0137] Taking a partition including 20*20 pixels, that is, 400 pixels as an example, according to the size of the compensation data, the compensation data of the 400 pixels in the target gray scale in the partition can be divided into N intervals (or regions). The compensation data of all sub-pixels in each interval in the target gray scale can be replaced by the same center value, that is, one interval corresponds to one center value. The present application does not limit the way of calculating the center value, for example, the commonly used LBG algorithm can be used to calculate the center value. For example, in some examples, for any one interval, the average, median or mode of the compensation data of the sub-pixels in the target gray scale contained in the interval can be calculated, and the average, median or mode of the compensation data of the sub-pixels in the target gray scale contained in the interval is taken as the center value of the interval.

[0138] S402, for any one sub-pixel in the partition, the index value corresponding to the sub-pixel is generated according to the interval to which the compensation data of the sub-pixel belongs.

[0139] In S402, the interval to which the compensation data of each sub-pixel belongs is known. Different intervals can correspond to different index values, for example, interval A corresponds to index value a1, interval B corresponds to index value b1, and interval C corresponds to index value c1. The role of the index value is that after the sub-pixel is assigned an index value, the interval to which the sub-pixel belongs and the corresponding center value can be accurately determined according to the index value corresponding to the sub-pixel. For example, when the index value corresponding to the sub-pixel is b1, it can be known that the sub-pixel belongs to interval B, and the center value corresponding to the sub-pixel is the center value of interval B, which is convenient for subsequent decompression.

[0140] For any one partition, the compensation data compressed by the partition includes the center values of the intervals and the index values corresponding to the sub-pixels in the partition.

[0141] Correspondingly, the data processing method of the display panel can further include the following step S403.

[0142] S403, for any one partition, the center values of the intervals in the partition and the index values corresponding to the sub-pixels in the partition are stored in the storage unit.

[0143] For any one partition, the center values of the intervals in the partition and the index values corresponding to the sub-pixels in the partition are stored in the storage unit.

[0144] In this way, the target vector quantization algorithm is applied to compress the compensation data. On the one hand, the compensation data of all sub-pixels in each interval at the target gray level is replaced by the same center value, which can greatly reduce the data amount and save the storage space. On the other hand, the compensation data can be classified and compressed according to the data size, which can improve the compression precision of the compensation data, better preserve the original data characteristics, reduce the distortion of the compressed compensation data, and further improve the Demura compensation effect.

[0145] It should be noted that when the target vector compression algorithm uses the initial cluster number adjustment coefficient to compress the compensation data of the partition, the process is similar to the above steps S401 and S402, which will not be repeated here.

[0146] In some specific examples, one partition can include sub-pixels of multiple colors, such as red sub-pixels, green sub-pixels, and blue sub-pixels. Correspondingly, S401 can specifically include the following steps:

[0147] For any i-th color sub-pixel in the partition, the compensation data of the plurality of i-th color sub-pixels in the partition at the target gray level is divided into N intervals, and the center value of the i-th color sub-pixel in each interval is determined according to the compensation data of the i-th color sub-pixel in each interval at the target gray level, i is a positive integer, 1≤i≤N. N=2K K is a target cluster number adjustment coefficient, K and N are positive integers.

[0148] In S401, for any one partition, compensation data of multiple red sub-pixels in the partition at the target gray level can be divided into N intervals, and a center value corresponding to a red sub-pixel of each interval is determined according to compensation data of the red sub-pixel at the target gray level contained in each interval. Compensation data of multiple green sub-pixels in the partition at the target gray level can be divided into N intervals, and a center value corresponding to a green sub-pixel of each interval is determined according to compensation data of the green sub-pixel at the target gray level contained in each interval. Compensation data of multiple blue sub-pixels in the partition at the target gray level can be divided into N intervals, and a center value corresponding to a blue sub-pixel of each interval is determined according to compensation data of the blue sub-pixel at the target gray level contained in each interval.

[0149] Correspondingly, S402, for any one sub-pixel in the partition, a subscript value corresponding to the sub-pixel is generated according to the interval to which the compensation data of the sub-pixel belongs, which can specifically include the following steps:

[0150] For any one i-th color sub-pixel in the partition, a subscript value corresponding to the i-th color sub-pixel is generated according to the interval to which the compensation data of the i-th color sub-pixel belongs.

[0151] Wherein, the interval to which the compensation data of each red sub-pixel belongs is known, the interval to which the compensation data of each green sub-pixel belongs is known, and the interval to which the compensation data of each blue sub-pixel belongs is known. Then, for each red sub-pixel, a subscript value corresponding to the red sub-pixel can be generated according to the interval to which the compensation data of the red sub-pixel belongs. For each green sub-pixel, a subscript value corresponding to the green sub-pixel can be generated according to the interval to which the compensation data of the green sub-pixel belongs. For each blue sub-pixel, a subscript value corresponding to the blue sub-pixel can be generated according to the interval to which the compensation data of the blue sub-pixel belongs.

[0152] Figure 5 Another flowchart of the data processing method of the display panel provided by the embodiments of the present application is shown in FIG. 5B. Figure 5 As shown in FIG. 5B, according to some embodiments of the present application, optionally, before S403, for any one partition, the center values of each interval in the partition and the subscript values corresponding to each sub-pixel in the partition are stored in the storage unit, the data processing method of the display panel can further include the following steps S501 and / or S502.

[0153] S501, limit the bit number of the center value to a second bit number, the second bit number is less than the first bit number.

[0154] For example, in some examples, the first number of bits can be 8 bits, and the second number of bits can be less than 8 bits, such as 4 bits or 5 bits, etc. When the center value (or compensation data) is 8 bits, the data range of the center value (or compensation data) is large. When the number of bits of the center value is limited to 4 bits or 5 bits, the data range of the center value becomes small, and thus the data amount of the center value also becomes small, thereby further reducing the data amount of the center value and further reducing the storage cost of the storage unit.

[0155] For example, in some specific embodiments, the second number of bits can be 4 bits, the highest bit is a sign bit, and the sign is ±, such as ±0000-±1111, that is, the gray scale compensation interval is ±15, and the range exceeding the interval directly overflows. For example, in some specific embodiments, the second number of bits can be 5 bits, the highest bit is a sign bit, and the sign is ±, such as ±00000-±11111, that is, the gray scale compensation interval is ±31, and the range exceeding the interval directly overflows.

[0156] S502, limit the number of bits of the subscript value to a third number of bits, the third number of bits being less than the first number of bits.

[0157] Similarly, the number of bits of the subscript value can also be limited to less than the first number of bits, such as 4 bits or 5 bits, etc. When the number of bits of the subscript value is limited to 4 bits or 5 bits, the data range of the subscript value becomes small, and thus the data amount of the subscript value also becomes small, thereby further reducing the data amount of the subscript value and further reducing the storage cost of the storage unit.

[0158] In some examples, the original number of bits (or initial number of bits) of the subscript value can be the first number of bits, that is, the number of bits of the subscript value can be limited from the first number of bits to less than the first number of bits. In other examples, the original number of bits (or initial number of bits) of the subscript value can also be greater than the first number of bits, that is, the number of bits of the subscript value can be limited from greater than the first number of bits to less than the first number of bits. In yet other examples, the number of bits of the subscript value can also be directly limited to less than the first number of bits when the subscript value is generated, and the embodiments of the present application do not limit this.

[0159] For example, in some specific embodiments, the third number of bits can be 4 bits, the highest bit is a sign bit, and the sign is ±, such as ±0000-±1111, that is, ±15, and the range exceeding the interval directly overflows. For example, in some specific embodiments, the third number of bits can be 5 bits, the highest bit is a sign bit, and the sign is ±, such as ±00000-±11111, that is, ±31, and the range exceeding the interval directly overflows.

[0160] The following takes N=16 and the number of bits of the subscript value as 4 bits as an example for description.

[0161] Table 1 schematically shows the center values of 16 intervals and the subscript values corresponding to each center value.

[0162] Table 1

[0163]

[0164] As shown in Table 1, in some examples, the compensation data of the multiple sub-pixels in each partition at the target gray scale tie point can be divided into 16 intervals, and A-Q represent the center values of the 16 intervals, respectively. Each center value can correspond to an index value (or a label value). For example, the center value A corresponds to the index value 0, the center value B corresponds to the index value 1, and so on, and the center value Q corresponds to the index value 15. Each sub-pixel in the partition can be assigned an index value, for example, 20*20 pixels in the partition can be assigned 400 index values, and the set of index values can be denoted as index. The set of center values can be denoted as value.

[0165] Correspondingly, S403, for any one partition, the center values of each interval in the partition and the index values corresponding to each sub-pixel in the partition are stored in the storage unit, which can specifically include the following steps:

[0166] The center values of each interval in the partition after bit limitation and / or the index values of each sub-pixel in the partition after bit limitation are stored in the storage unit.

[0167] Specifically, the center values of each interval in the partition after bit limitation and the index values of each sub-pixel in the partition after bit limitation can be stored in the storage unit. Alternatively, the center values of each interval in the partition and the index values corresponding to each sub-pixel in the partition are stored in the storage unit. Alternatively, the center values of each interval in the partition and the index values of each sub-pixel in the partition after bit limitation are stored in the storage unit.

[0168] That is, at least one of the center values and the index values can be subjected to bit limitation, which is not limited in the embodiments of the present application.

[0169] In this way, by limiting the bit number of the center values and / or the index values, the data range of the center values and / or the index values can be further reduced, and the data amount of the center values and / or the index values can also be reduced, thereby further reducing the data amount of the center values, and further reducing the storage cost of the storage unit.

[0170] In some specific embodiments, the third bit number can be less than the second bit number. For example, the bit number of the center values can be limited to 5 bits, and the bit number of the index values can be limited to 4 bits. In this way, the data range of the index values can be greatly reduced, the data amount of the index values is further reduced, the storage space is saved, and the storage cost is reduced.

[0171] Figure 6Another flowchart of S202 in the data processing method of the display panel is provided for the embodiments of the present application. As shown in Figure 6 According to some embodiments of the present application, the step of S202, decompressing the compensation data after partition compression to obtain compensation data after partition decompression, can optionally include the following steps S601 and S602.

[0172] S601, for any one sub-pixel in the partition, determining the center value corresponding to the sub-pixel at the target gray scale according to the correspondence between the index value and the center value at the target gray scale and the index value of the sub-pixel.

[0173] As mentioned before, different center values (or intervals) can correspond to different index values, as shown in Table 1, the correspondence between the index value and the center value at the target gray scale can be established in advance. For any one sub-pixel in the partition, the center value corresponding to the sub-pixel at the target gray scale can be determined according to the index value of the sub-pixel after decompression and the correspondence between the index value and the center value at the target gray scale.

[0174] S602, taking the center value corresponding to the sub-pixel as the compensation data of the sub-pixel at the target gray scale.

[0175] For any one sub-pixel in the partition, after obtaining the center value corresponding to the sub-pixel at the target gray scale, the center value corresponding to the sub-pixel can be taken as the compensation data of the sub-pixel at the target gray scale. The compensation data can be used to correct the gray scale to be displayed by the sub-pixel, realizing Demura compensation.

[0176] Figure 7 Another flowchart of S102 in the data processing method of the display panel is provided for the embodiments of the present application. As shown in Figure 7 According to some embodiments of the present application, the step of S102, compressing the compensation data of the multiple partitions based on the target vector compression algorithm to obtain the compensation data after compression of the multiple partitions, can optionally include the following steps S701 to S703.

[0177] S701, for any one partition, determining the background data corresponding to the partition according to the gray scale displayed by the partition.

[0178] In some examples, the background data includes but is not limited to the gray scale expected to be displayed by the partition. For example, for the compensation data of the partition at the target gray scale, the background data can be the target gray scale. Taking 32 gray scales as an example for the gray scale expected to be displayed by the partition (i.e. the target gray scale), the background data can be 32 gray scales.

[0179] S702, removing the background data from the compensation data of the partition to obtain the compensation data after removing the background data of the partition.

[0180] That is, the background data is subtracted from the compensation data of the partition to obtain the compensation data after the background data is removed from the partition.

[0181] It should be noted that when the number of bits of the compensation data and the background data is different, the number of bits of the background data needs to be converted to the same number of bits as the compensation data before calculation. Taking the compensation data of one of the sub-pixels of the partition as 129 and the background data as 32 gray scales as an example, for example, the number of bits of the compensation data is 10 bits, and the number of bits of the background data is 8 bits, the background data needs to be converted to 10 bits, that is, 32*4=128. Then, 129-128=1 is obtained, so that the compensation data after the background data is removed from the sub-pixel is obtained.

[0182] S703, based on the target vector compression algorithm, the compensation data after the background data is removed from the partition is compressed to obtain the compensation data after the partition is compressed.

[0183] In S703, the compensation data after the background data is removed from the partition can be compressed based on the target vector compression algorithm to obtain the compensation data after the partition is compressed. The specific compression process of the target vector compression algorithm has been described in detail above, and will not be repeated here.

[0184] In this way, by removing the background data from the compensation data of the partition, the compensation data after the background data is removed from the partition is obtained, which can further reduce the data amount of the compensation data.

[0185] Figure 8 Another flowchart of the data processing method of the display panel provided by the embodiments of the present application is provided. As shown in the figure, Figure 8 According to some embodiments of the present application, the data processing method of the display panel can further include the following step S801 before the step of S703, based on the target vector compression algorithm, the compensation data after the background data is removed from the partition is compressed to obtain the compensation data after the partition is compressed.

[0186] S801, based on the block compression algorithm, the compensation data after the background data is removed from the partition is mean compressed to obtain the compensation data after the partition is mean compressed.

[0187] Among them, the block compression is also called Block compression. According to the compression requirement, 1*1, 1*2, 2*1 or 2*2 Block (compression ratio) can be selected to perform mean compression on the brightness compensation data. For example, for a group of data of 2 rows and 4 columns The block1*2 compression is to take the mean value once every row and every two columns to obtain become 2 rows and 2 columns.

[0188] Correspondingly, the step S703 of compressing the compensation data after removing the background data of the partition based on the target vector compression algorithm to obtain the compressed compensation data of the partition can specifically include the following steps:

[0189] The compensation data after the mean compression of the partition is compressed based on the target vector compression algorithm to obtain the compressed compensation data of the partition.

[0190] That is, the compensation data can be compressed in blocks first, and then the compensation data after the block compression is compressed by vector quantization. In this way, it can be applied to a situation with a higher compression ratio requirement.

[0191] In this way, the mean compression of the compensation data of each partition is performed based on the block compression algorithm first, which can further reduce the data amount of the compensation data, save storage space, and reduce storage costs.

[0192] According to some embodiments of the present application, optionally, the cluster number adjustment coefficients corresponding to at least part of the partitions can be different.

[0193] In this way, for the compensation data of different partitions, by flexibly adjusting the target cluster number adjustment coefficients corresponding to each partition, the compensation data of each partition can be compressed according to the respective appropriate target cluster number adjustment coefficients, so that the compensation data of each partition has a larger compression ratio under the condition of meeting the compression precision requirement, and the data amount of each partition after compression is greatly reduced.

[0194] Based on the data processing method of the display panel provided in the above embodiments, correspondingly, the present application also provides a specific implementation mode of a data processing apparatus of the display panel. Please refer to the following embodiments.

[0195] Figure 9 A structural schematic diagram of the data processing apparatus of the display panel provided in the embodiments of the present application. As shown in the figure, Figure 9 The data processing apparatus 90 of the display panel provided in the embodiments of the present application includes the following modules:

[0196] The acquisition module 901 is configured to acquire compensation data of a plurality of partitions.

[0197] The first compression module 902 is configured to compress the compensation data of the plurality of partitions based on a target vector compression algorithm to obtain compensation data of the plurality of partitions after compression.

[0198] The data processing apparatus of the display panel provided in the embodiments of the present application obtains compensation data of multiple partitions in the display panel; and performs compression on the compensation data of the multiple partitions based on a target vector compression algorithm to obtain compressed compensation data of the multiple partitions. The embodiments of the present application apply the target vector quantization algorithm to compress the compensation data of the multiple partitions, can classify and compress the compensation data of the multiple partitions according to the data size of the compensation data of each partition, improve the compression precision of the compensation data, better retain the original data characteristics, reduce the distortion of the compressed compensation data, and further improve the Demura compensation effect.

[0199] In some embodiments, the data processing apparatus 90 of the display panel provided in the embodiments of the present application further includes a determination module configured to, for the compensation data of any one partition, perform compression on the compensation data of the partition based on the target vector compression algorithm of the initial cluster number adjustment coefficient to obtain compressed compensation data of the partition; perform decompression on the compressed compensation data of the partition to obtain decompressed compensation data of the partition; compare the compensation data of the partition before compression with the decompressed compensation data of the partition, and determine a target cluster number adjustment coefficient according to a comparison result. The first compression module 902 is specifically configured to perform compression on the compensation data of the partition based on the target vector compression algorithm of the target cluster number adjustment coefficient to obtain the compressed compensation data of the partition.

[0200] In some embodiments, the determination module is specifically configured to calculate a sum of absolute values of differences between the compensation data of the multiple sub-pixels in the partition before compression and the compensation data of the multiple sub-pixels in the partition after decompression; calculate a difference rate according to the sum and the number of the sub-pixels in the partition; when the difference rate is greater than a preset threshold, increase the cluster number adjustment coefficient until the difference rate is less than or equal to the preset threshold to obtain the target cluster number adjustment coefficient; and / or when the difference rate is less than the preset threshold, decrease the cluster number adjustment coefficient until the difference rate is greater than the preset threshold, and take the cluster number adjustment coefficient adjusted last time when the difference rate is less than or equal to the preset threshold as the target cluster number adjustment coefficient.

[0201] In some embodiments, the determination module is specifically configured to calculate the sum of the absolute values of the differences between the compensation data of the multiple sub-pixels in the partition before compression and the compensation data of the multiple sub-pixels in the partition after decompression according to the following expression:

[0202]

[0203] wherein D represents the sum, DataS(k) represents the compensation data of the kth sub-pixel in the partition before compression, DataD(k) represents the compensation data of the kth sub-pixel in the partition after decompression, n represents the number of the sub-pixels in the partition, abs represents the absolute value operation, k and n are both positive integers, and 1≤k≤n.

[0204] In some embodiments, the determining module is specifically configured to calculate the difference rate according to the following expression:

[0205] ratio = 100% * D / n

[0206] wherein, ratio represents the difference rate, n represents the number of sub-pixels in the partition, and n is a positive integer.

[0207] In some embodiments, the adjustment step of the cluster number adjustment coefficient comprises 1.

[0208] In some embodiments, the compensation data of the plurality of partitions comprises first compensation data corresponding to a first target gray scale and second compensation data corresponding to a second target gray scale, the first target gray scale is different from the second target gray scale; the preset threshold corresponding to the first target gray scale is different from the preset threshold corresponding to the second target gray scale; and / or, the difference rate is determined according to the cumulative sum, the number of sub-pixels in the partition, and the adjustment coefficient, the adjustment coefficient corresponding to the first target gray scale is different from the adjustment coefficient corresponding to the second target gray scale.

[0209] In some embodiments, the determining module is specifically configured to calculate the difference rate according to the following expression:

[0210] ratio = 100% * D / n * p

[0211] wherein, ratio represents the difference rate, n represents the number of sub-pixels in the partition, p is the adjustment coefficient, p ≥ 1, and n is a positive integer.

[0212] In some embodiments, the first target gray scale is smaller than the second target gray scale; the preset threshold corresponding to the first target gray scale is smaller than the preset threshold corresponding to the second target gray scale, and / or, the adjustment coefficient corresponding to the first target gray scale is smaller than the adjustment coefficient corresponding to the second target gray scale.

[0213] In some embodiments, the first compression module 902 is specifically configured to, for any one partition, divide the compensation data of the plurality of sub-pixels in the partition at a target gray scale into N intervals, and determine the center value of each interval according to the compensation data of the sub-pixels contained in each interval, the target gray scale being any one gray scale binding point, N = 2 K , K is the target cluster number adjustment coefficient, and K and N are both positive integers; for any one sub-pixel in the partition, the index value corresponding to the sub-pixel is generated according to the interval to which the compensation data of the sub-pixel belongs. The compressed compensation data of the partition comprises the center value of each interval and the index value corresponding to each sub-pixel in the partition. The data processing device 90 of the display panel provided in the embodiments of the present application further comprises a storage module configured to, for any one partition, store the center value of each interval in the partition and the index value corresponding to each sub-pixel in the partition into a storage unit.

[0214] In some embodiments, the data processing apparatus 90 of the display panel provided by the embodiments of the present application further comprises a limiting module, configured to limit the number of bits of the center value to a second number of bits, the second number of bits being less than the first number of bits; and / or limit the number of bits of the subscript value to a third number of bits, the third number of bits being less than the first number of bits. The storage module is specifically configured to store the center value with the limited number of bits of each interval in the partition and / or the subscript value with the limited number of bits of each sub-pixel in the partition into the storage unit.

[0215] In some embodiments, the determining module is specifically configured to, for any one sub-pixel in the partition, determine the corresponding center value of the sub-pixel at the target gray scale according to the corresponding relationship between the subscript value and the center value at the target gray scale and the subscript value of the sub-pixel; and take the corresponding center value of the sub-pixel as the compensation data of the sub-pixel at the target gray scale.

[0216] In some embodiments, the first compression module 902 is specifically configured to, for any one partition, determine the corresponding background data of the partition according to the gray scale displayed by the partition; remove the background data from the compensation data of the partition to obtain the compensation data of the partition after removing the background data; and compress the compensation data of the partition after removing the background data based on a target vector compression algorithm to obtain the compressed compensation data of the partition.

[0217] In some embodiments, the data processing apparatus 90 of the display panel provided by the embodiments of the present application further comprises a second compression module, configured to perform mean compression on the compensation data of the partition after removing the background data based on a block compression algorithm to obtain the mean compressed compensation data of the partition. The first compression module 902 is specifically configured to compress the mean compressed compensation data of the partition based on a target vector compression algorithm to obtain the compressed compensation data of the partition.

[0218] In some embodiments, the target vector compression algorithm comprises an LBG algorithm.

[0219] In some embodiments, the target clustering number adjustment coefficients of at least part of the partitions are different.

[0220] Figure 9 Each module / unit in the data processing apparatus of the display panel has the function of each step in the data processing method of the display panel provided by the above-mentioned method embodiments, and can achieve its corresponding technical effects. For the sake of brevity, it will not be described here.

[0221] Based on the data processing method of the display panel provided by the above-mentioned embodiments, correspondingly, the present application also provides a specific implementation mode of an electronic device. Please refer to the following embodiments.

[0222] Figure 10A hardware structure schematic diagram of an electronic device provided by an embodiment of the present application is shown.

[0223] The electronic device can include a processor 1001 and a memory 1002 storing computer program instructions.

[0224] Specifically, the processor 1001 described above can include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or can be configured as one or more integrated circuits that implement one or more embodiments of the present application.

[0225] The memory 1002 can include a mass storage for data or instructions. By way of example and not limitation, the memory 1002 can 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. In one example, the memory 1002 can include a removable or non-removable (or fixed) media, or the memory 1002 is a non-volatile solid-state memory. The memory 1002 can be internal or external to the electronic device.

[0226] In one example, the memory 1002 can be a read-only memory (ROM). In one example, the ROM can be a mask-programmed ROM, a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), an electrically alterable ROM (EAROM), or a flash memory, or a combination of two or more of these.

[0227] The memory 1002 can include a read-only memory (ROM), a random access memory (RAM), a disk storage medium device, an optical storage medium device, a flash memory device, an electrical, optical, or other physical / tangible memory storage device. Thus, generally, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions that, when executed (e.g., by one or more processors), are operable to perform operations described with reference to methods according to an aspect of the present application.

[0228] The processor 1001 implements the methods / steps in the above-described method embodiments by reading and executing the computer program instructions stored in the memory 1002, and achieves the corresponding technical effects achieved by the method embodiments executing their methods / steps, which are not described herein for brevity.

[0229] In one example, the electronic device can further include a communication interface 1003 and a bus 1010. As shown, the processor 1001, the memory 1002, and the communication interface 1003 are connected by the bus 1010 and complete communication with each other. Figure 10

[0230] The communication interface 1003 is mainly used to realize the communication between the modules, devices, units and / or equipment in the embodiments of the present application.

[0231] The bus 1010 includes hardware, software or both to couple components of the electronic device to each other. By way of example, and not limitation, the bus can include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an InfiniBand interconnect, a Low Pin Count (LPC) bus, a memory bus, a Micro Channel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association local (VLB) bus, or another suitable bus or combination of two or more of these. Where appropriate, the bus 1010 can include one or more buses. Although the present embodiments describe and show a particular bus, the present application contemplates any suitable bus or interconnect.

[0232] In addition, in combination with the data processing method of the display panel in the above-mentioned embodiments, the present embodiments can provide a computer readable storage medium for implementation. The computer readable storage medium has computer program instructions stored thereon; the computer program instructions are executed by a processor to implement any one of the data processing methods of the display panel in the above-mentioned embodiments. Examples of the computer readable storage medium include non-transitory computer readable storage media, such as electronic circuits, semiconductor memory devices, ROM, random access memory, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks.

[0233] ​It is to be understood that the application is not limited to the particular configurations and processes described hereinabove and shown in the figures. For the sake of brevity, detailed descriptions of known methods and apparatuses are omitted so as to avoid obscuring the subject matter of the present application. In the above-described embodiments, several specific steps are described and illustrated as examples. However, the method processes of the present application are not limited to the specific steps described and illustrated herein, but can include any number of additional steps or changes in the order of the steps, or both, depending on the embodiment of the application.

[0234] The functional blocks shown in the above-described block diagrams 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, and the like. When implemented in software, the elements of the present application are program or code segments that are used to perform the required tasks. The program or code segments can be stored in a machine-readable medium or transmitted through a data signal carried in a carrier wave over a transmission medium or communication link. A "machine-readable medium" includes any medium that can store or transfer information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio frequency (RF) links, and the like. The code segments can be downloaded via computer networks such as the Internet, intranets, and the like.

[0235] It is also to be understood that the example embodiments described in the present application are based on a series of steps or apparatuses to describe some methods or systems. However, the present application is not limited to the order of the above steps, that is, the steps can be performed in the order mentioned in the embodiments, or in an order different from the embodiments, or several steps can be performed simultaneously.

[0236] The computer program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other processing device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other processing device to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0237] The above only is a specific implementation of the present application, and those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the above-described system, module and unit can refer to the corresponding process in the foregoing method embodiments, which will not be described herein. It should be understood that the protection scope of the present application is not limited to this, and any person skilled in the art can easily think of various equivalent modifications or replacements within the technical range disclosed in the present application, and these modifications or replacements shall be covered within the protection scope of the present application.

Claims

1. A data processing method of a display panel, characterized by, The display panel comprises a plurality of partitions, each of the partitions comprising at least one sub-pixel, and the method comprises: obtaining compensation data of the plurality of partitions; compressing the compensation data of the plurality of partitions based on a target vector compression algorithm to obtain compressed compensation data of the plurality of partitions; before the step of compressing the compensation data of the plurality of partitions based on the target vector compression algorithm to obtain compressed compensation data of the plurality of partitions, the method further comprises: for the compensation data of any one partition, compressing the compensation data of the partition based on the target vector compression algorithm with an initial cluster quantity adjustment coefficient to obtain compressed compensation data of the partition; decompressing the compressed compensation data of the partition to obtain decompressed compensation data of the partition; comparing the compensation data of the partition before compression with the decompressed compensation data of the partition, and determining a target cluster quantity adjustment coefficient according to a comparison result; the step of compressing the compensation data of the plurality of partitions based on the target vector compression algorithm to obtain compressed compensation data of the plurality of partitions specifically comprises: compressing the compensation data of the partition based on the target vector compression algorithm with the target cluster quantity adjustment coefficient to obtain compressed compensation data of the partition; the step of comparing the compensation data of the partition before compression with the decompressed compensation data of the partition, and determining a target cluster quantity adjustment coefficient according to a comparison result specifically comprises: calculating a cumulative sum of absolute values of differences between the compensation data of a plurality of sub-pixels in the partition before compression and the compensation data of the plurality of sub-pixels in the partition after decompression; calculating a difference rate according to the cumulative sum and the number of sub-pixels in the partition; when the difference rate is greater than a preset threshold, increasing the cluster quantity adjustment coefficient until the difference rate is less than or equal to the preset threshold to obtain the target cluster quantity adjustment coefficient; and / or, when the difference rate is less than a preset threshold, decreasing the cluster quantity adjustment coefficient until the difference rate is greater than the preset threshold, and taking the cluster quantity adjustment coefficient adjusted last time when the difference rate is less than or equal to the preset threshold as the target cluster quantity adjustment coefficient.

2. The method of claim 1, wherein, The cumulative sum of absolute values of differences between the compensation data of a plurality of sub-pixels in the partition before compression and the compensation data of the plurality of sub-pixels in the partition after decompression is calculated according to the following expression: wherein D represents the cumulative sum, DataS(k) represents the compensation data of the kth sub-pixel in the partition before compression, DataD(k) represents the compensation data of the kth sub-pixel in the partition after decompression, n represents the number of sub-pixels in the partition, abs represents an absolute value operation, k and n are both positive integers, and 1≤k≤n.

3. The method of claim 1, wherein, The difference rate is calculated according to the following expression: ratio=100%*D / n wherein ratio represents the difference rate, n represents the number of sub-pixels in the partition, and n is a positive integer.

4. The method of claim 3, wherein, The adjustment step of the cluster quantity adjustment coefficient comprises 1.

5. The method of claim 3, wherein, The compensation data of the plurality of partitions comprises first compensation data corresponding to a first target gray scale and second compensation data corresponding to a second target gray scale, the first target gray scale being different from the second target gray scale; The preset threshold corresponding to the first target gray scale is different from the preset threshold corresponding to the second target gray scale; Or, the difference rate is determined according to the cumulative sum, the number of sub-pixels in the partition, and an adjustment coefficient, the adjustment coefficient corresponding to the first target gray scale being different from the adjustment coefficient corresponding to the second target gray scale.

6. The method of claim 5, wherein, The difference rate is calculated according to the following expression: ratio = 100% * D / (n * p) Wherein, ratio represents the difference rate, n represents the number of sub-pixels in the partition, p is the adjustment coefficient, p ≥ 1, and n is a positive integer.

7. The method of claim 5, wherein, The first target gray scale is smaller than the second target gray scale; The preset threshold corresponding to the first target gray scale is smaller than the preset threshold corresponding to the second target gray scale.

8. The method of claim 5, wherein, The adjustment coefficient corresponding to the first target gray scale is smaller than the adjustment coefficient corresponding to the second target gray scale.

9. The method according to any one of claims 1 to 8, characterized in that, The step of compressing the compensation data of the partition based on the target vector compression algorithm of the target cluster number adjustment coefficient to obtain the compressed compensation data of the partition, specifically comprises: For any one of the partitions, the compensation data of the sub-pixels in the partition at a target gray level is divided into N intervals, and a center value of each interval is determined according to the compensation data of the sub-pixels in the target gray level contained in each interval, the target gray level being any one gray level binding point, and N=2 K K is the target cluster quantity adjustment coefficient, and K and N are positive integers. For any one sub-pixel in the partition, a subscript value corresponding to the sub-pixel is generated according to the interval to which the compensation data of the sub-pixel belongs; The compressed compensation data of the partition comprises the center value of each interval and the subscript value corresponding to each sub-pixel in the partition; The method further comprises: For any one of the partitions, the center value of each interval in the partition and the subscript value corresponding to each sub-pixel in the partition are stored in a storage unit.

10. The method of claim 9, wherein, Before the step of storing the center value of each interval in the partition and the subscript value corresponding to each sub-pixel in the partition in the storage unit, the method further comprises: The number of bits of the center value is limited to a second number of bits, the second number of bits being smaller than the first number of bits; And / or, the number of bits of the subscript value is limited to a third number of bits, the third number of bits being smaller than the first number of bits; The step of storing the center value of each interval in the partition and the subscript value corresponding to each sub-pixel in the partition in the storage unit, specifically comprises: The center value of each interval in the partition after limiting the number of bits and / or the subscript value of each sub-pixel in the partition after limiting the number of bits are stored in the storage unit.

11. The method of claim 9, wherein, The step of decompressing the compressed compensation data of the partition to obtain the decompressed compensation data of the partition, specifically comprises: For any one sub-pixel in the partition, a center value corresponding to the sub-pixel at the target gray scale is determined according to the correspondence between the subscript value and the center value at the target gray scale and the subscript value of the sub-pixel; The center value corresponding to the sub-pixel is taken as the compensation data of the sub-pixel at the target gray scale.

12. The method of claim 1, wherein, The step of compressing the compensation data of the multiple partitions based on the target vector compression algorithm to obtain the compressed compensation data of the multiple partitions specifically comprises: For any one of the partitions, background data corresponding to the partition is determined according to a gray scale displayed by the partition; The background data is removed from the compensation data of the partition to obtain compensation data of the partition after the background data is removed; The compensation data of the partition after the background data is removed is compressed based on the target vector compression algorithm to obtain compressed compensation data of the partition.

13. The method of claim 12, wherein, Before the step of compressing the compensation data of the partition after the background data is removed based on the target vector compression algorithm to obtain the compressed compensation data of the partition, the method further comprises: The compensation data of the partition after the background data is removed is mean compressed based on a block compression algorithm to obtain mean compressed compensation data of the partition; The step of compressing the compensation data of the partition after the background data is removed based on the target vector compression algorithm to obtain the compressed compensation data of the partition specifically comprises: The compensation data of the partition after the background data is removed is compressed based on the target vector compression algorithm to obtain the compressed compensation data of the partition.

14. The method of claim 1, wherein, The target vector compression algorithm comprises an LBG algorithm.

15. The method of claim 14, wherein, Target cluster quantity adjustment coefficients corresponding to at least some of the partitions are different.

16. A data processing apparatus of a display panel, characterized by, The display panel comprises multiple partitions, each of the partitions comprising at least one sub-pixel, and the device comprises: An acquisition module configured to acquire compensation data of the multiple partitions; A first compression module configured to compress the compensation data of the multiple partitions based on a target vector compression algorithm to obtain compressed compensation data of the multiple partitions; Before the step of compressing the compensation data of the multiple partitions based on the target vector compression algorithm to obtain the compressed compensation data of the multiple partitions, the method further comprises: For compensation data of any one of the partitions, the compensation data of the partition is compressed based on the target vector compression algorithm of an initial cluster quantity adjustment coefficient to obtain compressed compensation data of the partition; The compressed compensation data of the partition is decompressed to obtain decompressed compensation data of the partition; The compensation data of the partition before compression and the decompressed compensation data of the partition are compared, and a target cluster quantity adjustment coefficient is determined according to a comparison result; The step of compressing the compensation data of the multiple partitions based on the target vector compression algorithm to obtain the compressed compensation data of the multiple partitions specifically comprises: The compensation data of the partition is compressed based on the target vector compression algorithm of the target cluster quantity adjustment coefficient to obtain the compressed compensation data of the partition; The step of comparing the compensation data of the partition before compression and the decompressed compensation data of the partition and determining a target cluster quantity adjustment coefficient according to a comparison result specifically comprises: calculating a sum of absolute values of differences between the compensation data of the plurality of sub-pixels in the partition before compression and the compensation data of the plurality of sub-pixels in the partition after decompression; calculating a difference rate according to the sum and a number of sub-pixels in the partition; when the difference rate is greater than a preset threshold, increasing a cluster number adjustment coefficient until the difference rate is less than or equal to the preset threshold, to obtain a target cluster number adjustment coefficient; and / or, when the difference rate is less than the preset threshold, decreasing the cluster number adjustment coefficient until the difference rate is greater than the preset threshold, and taking the cluster number adjustment coefficient adjusted last time when the difference rate is less than or equal to the preset threshold as the target cluster number adjustment coefficient.

17. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program is executed by the processor to implement the steps of the data processing method of the display panel according to any one of claims 1 to 14.

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