CN116682350A

CN116682350A - Data processing method and device for display panel and computer readable storage medium

Info

Publication number: CN116682350A
Application number: CN202310752763.0A
Authority: CN
Inventors: 杨攀
Original assignee: Kunshan Govisionox Optoelectronics Co Ltd
Current assignee: Kunshan Govisionox Optoelectronics Co Ltd
Priority date: 2023-06-25
Filing date: 2023-06-25
Publication date: 2023-09-01

Abstract

The embodiment of the application provides a data processing method and device of a display panel and a computer readable storage medium, wherein the display panel comprises a plurality of partitions, each partition comprises at least one sub-pixel, and the data processing method of the display panel comprises the following steps: acquiring compensation data of a plurality of partitions; and compressing the compensation data of the multiple partitions based on a target vector compression algorithm to obtain the compressed compensation data of the multiple partitions. The embodiment of the application can improve the compression precision of the compensation data and reduce the distortion degree of the compressed compensation data.

Description

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

Technical Field

The present application relates to the field of display technologies, and in particular, to a method and an apparatus for processing data of a display panel, and a computer readable storage medium.

Background

The phenomenon of uneven brightness and chromaticity of the display panel can occur due to the influence of factors such as technology, materials, equipment and the like in the production process, and the phenomenon is called Mura. At present, the mainstream Demura method is mainly an external optical compensation method, namely, capturing brightness data of a display panel through a camera, calculating compensation data through a Demura algorithm, and writing the compensation data into a storage unit after data compression, so that brightness compensation of the display panel is realized.

However, the brightness compensation of the display panel in the related art is poor.

Disclosure of Invention

The embodiment of the application provides a data processing method and device of a display panel and a computer readable storage medium, which can improve the compression precision of compensation data and reduce the distortion degree of the compressed compensation data.

In a first aspect, an embodiment of the present application provides a data processing method of a display panel, where the display panel includes a plurality of partitions, each partition includes at least one subpixel, and the data processing method of the display panel includes: acquiring compensation data of a plurality of partitions; and compressing the compensation data of the multiple partitions based on a target vector compression algorithm to obtain the compressed compensation data of the multiple partitions.

According to an embodiment 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 the compressed compensation data of the plurality of partitions, the data processing method of the display panel may further include: for the compensation data of any partition, compressing the compensation data of the partition based on a target vector compression algorithm of an initial clustering quantity adjustment coefficient to obtain the compensation data after the partition is compressed; decompressing the compensation data after the partition compression to obtain the compensation data after the partition decompression; comparing the compensation data of the subarea before compression with the compensation data after decompression of the subarea, and determining a target cluster quantity adjustment coefficient according to a comparison result; compressing the compensation data of the plurality of partitions based on a target vector compression algorithm to obtain the compressed compensation data of the plurality of partitions, wherein the method specifically comprises the following steps: and compressing the compensation data of the partition based on a target vector compression algorithm of the target cluster quantity adjustment coefficient to obtain the compensation data after the partition is compressed.

Therefore, the compensation data of each partition can be compressed according to the corresponding target cluster quantity adjustment coefficient by flexibly adjusting the target cluster quantity adjustment coefficient corresponding to each partition according to the corresponding cluster quantity adjustment coefficient, so that the compensation data of each partition has a larger compression ratio under the condition of meeting the compression precision requirement, and the compressed data quantity of each partition is reduced to a larger extent.

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 after decompression of the partition and determining the target cluster number adjustment coefficient according to the comparison result may specifically include: calculating a sum of absolute values of differences between compensation data before compression of the plurality of sub-pixels in the partition and compensation data after decompression of the plurality of sub-pixels in the partition; calculating a difference rate according to the number of sub-pixels in the sum and the partition; when the difference rate is larger than a preset threshold, increasing the clustering quantity adjusting coefficient until the difference rate is smaller than or equal to the preset threshold, and obtaining a target clustering quantity adjusting coefficient; and/or when the difference rate is smaller than a preset threshold, reducing the cluster number adjustment coefficient until the difference rate is larger than the preset threshold, and taking the last-time adjusted cluster number adjustment coefficient with the difference rate smaller than or equal to the preset threshold as the target cluster number adjustment coefficient.

Thus, when the difference rate is greater than a preset threshold, the cluster number adjustment coefficient is increased, and/or when the difference rate is less than the preset threshold, the cluster number adjustment coefficient which is more suitable for each partition can be obtained by reducing the cluster number adjustment coefficient. The compensation data is compressed by utilizing the more proper clustering quantity adjusting coefficient of each partition, 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 quantity of each partition after compression is reduced to a larger extent.

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 before compression of the plurality of sub-pixels in the partition and the compensation data after decompression of the plurality of sub-pixels in the partition is calculated according to the following expression:

wherein D represents summation, dataS (k) represents compensation data before compression of kth sub-pixel in the partition, dataD (k) represents compensation data after decompression of kth sub-pixel in the partition, n represents the number of sub-pixels in the partition, abs represents absolute value operation, k and n are positive integers, and k is more than or equal to 1 and less than or equal to n.

Thus, by the expression, the sum of absolute values of differences between the compensation data before the compression of the plurality of sub-pixels in the partition and the compensation data after the decompression of the plurality of sub-pixels in the partition can be obtained quickly and accurately.

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

ratio＝100％*D/n

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

Thus, the difference rate is obtained by the expression, and the difference between the compensation data of the subarea before compression and the compensation data after subarea decompression can be objectively and accurately reflected.

According to any of the foregoing embodiments of the first aspect of the present application, the adjustment step size of the cluster number adjustment coefficient includes 1.

Thus, when the adjustment step length of the cluster number adjustment coefficient is 1, for example, inaccuracy of the target cluster number adjustment coefficient which is finally adopted due to a large adjustment step length setting of the cluster number adjustment coefficient can be avoided, for example, overlong time spent in determining the target cluster number adjustment coefficient due to a small adjustment step length setting of the cluster number adjustment coefficient can be avoided.

According to any one of the foregoing embodiments of the first aspect of the present application, the compensation data of the plurality of partitions includes first compensation data of the plurality of partitions corresponding to a first target gray level and second compensation data of the plurality of partitions corresponding to a second target gray level, the first target gray level being different from the second target gray level; the preset threshold corresponding to the first target gray level is different from the preset threshold corresponding to the second target gray level; and/or the difference rate is determined according to the sum, the number of the sub-pixels in the partition and the adjustment coefficient, and the adjustment coefficient corresponding to the first target gray level is different from the adjustment coefficient corresponding to the second target gray level.

In this way, the preset threshold values and/or the adjustment coefficients corresponding to different gray scales are different, so that the adjustment coefficients of the target cluster quantity obtained under different gray scales can be different. Therefore, the compensation data with different gray scales can be compressed based on different target cluster quantity adjustment coefficients, so that the compensation data with different gray scales has a larger compression ratio under the condition that the compression precision requirement is met, and the compressed data quantity is reduced to a larger extent.

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 is equal to or greater than 1, and n is a positive integer.

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

Therefore, when the gray level is higher, the judgment standard of the difference rate can be widened appropriately, so that smaller clustering quantity adjustment coefficients are obtained, compensation data are compressed as much as possible under the condition that the compression precision requirement is met, and the data quantity after compression is reduced to a large extent.

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 partition based on the target vector compression algorithm of the target cluster number adjustment coefficient to obtain the compensation data after the partition compression may specifically include: for any one partition, dividing the compensation data of a plurality of sub-pixels in the partition in target gray scales into N sections, and determining the central value of each section according to the compensation data of the sub-pixels in the target gray scales contained in each section, wherein the target gray scales are any one gray scale binding point, and N=2 ^K K is a target cluster quantity adjustment coefficient, and K and N are positive integers; for any one sub-pixel in the subarea, generating a lower standard value corresponding to the sub-pixel according to the interval to which the compensation data of the sub-pixel belongs; the compensation data after the partition compression comprises a central value of each interval and a lower index value corresponding to each sub-pixel in the partition; the data processing method of the display panel further comprises the following steps: for any one partition, the center value of each interval in the partition and the index value corresponding to each sub-pixel in the partition are stored in a storage unit.

Therefore, the embodiment of the application compresses the compensation data by applying the target vector quantization algorithm, on one hand, the compensation data of all the sub-pixels in each interval when the target gray level is realized is replaced by the same central value, thus greatly reducing the data quantity and saving the storage space; on the other hand, the compensation data can be classified and compressed according to the data size, the compression precision of the compensation data is improved, the original data characteristics are better reserved, the distortion degree of the compressed compensation data is reduced, and the Demura compensation effect is further improved.

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 section in the partition and the index value corresponding to each sub-pixel in the partition in the storage unit, the data processing method of the display panel may further include: limiting the number of bits of the central value from a first number of bits 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; the step of storing the center value of each section in the partition and the subscript value corresponding to each sub-pixel in the partition in the storage unit specifically includes: and storing the central value after limiting the bit number of each interval in the partition and/or the subscript value after limiting the bit number of each sub-pixel in the partition into a storage unit.

Therefore, the data range of the center value and/or the lower index value can be further reduced by limiting the bit number of the center value and/or the lower index value, and the data volume of the center value and/or the lower index value can be further reduced, so that the data volume of the center value is further reduced, and the storage cost of the storage unit is further reduced.

According to any one of the foregoing embodiments of the first aspect of the present application, the step of decompressing the compensated data after the partition compression to obtain the compensated data after the partition decompression may specifically include: for any sub-pixel in the subarea, determining a corresponding central value of the sub-pixel in the target gray level according to the corresponding relation between the lower standard value and the central value in the target gray level and the lower standard value of the sub-pixel; and taking the central value corresponding to the sub-pixel as compensation data of the sub-pixel in the target gray scale.

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 the compressed compensation data of the plurality of partitions may specifically include: for any one partition, determining background data corresponding to the partition according to gray scales displayed by the partition; removing background data from the compensation data of the partition to obtain the compensation data of the partition after removing the background data; and compressing the compensation data after the background data is removed from the partition based on a target vector compression algorithm to obtain the compensation data after the partition is compressed.

In this way, by removing the background data from the compensation data of the partition, the compensation data after the partition removes the background data is obtained, and the data amount of the compensation data can be further reduced.

According to any one of the foregoing embodiments of the first aspect of the present application, before the step of compressing the compensation data after the background data is removed from the partition based on the target vector compression algorithm to obtain the compensation data after the partition compression, the data processing method of the display panel may further include: based on a block compression algorithm, carrying out mean compression on the compensation data after background data is removed from the partition, and obtaining the compensation data after the partition mean compression; based on a target vector compression algorithm, compressing the compensation data after removing the background data from the partition to obtain the compensation data after compressing the partition, which specifically comprises the following steps: and compressing the compensation data after the partition mean value compression based on a target vector compression algorithm to obtain the compensation data after the partition compression.

Therefore, the compensation data of each partition is subjected to mean value compression based on the block compression algorithm, so that the data volume of the compensation data can be further reduced, the storage space is saved, and the storage cost is reduced.

According to any of the foregoing embodiments of the first aspect of the present application, the target vector compression algorithm may comprise an LBG algorithm.

Therefore, the LBG algorithm is applied to compress the compensation data of the multiple partitions, the compensation data of each partition can be classified and compressed according to the data size of the compensation data of each partition, the compression precision of the compensation data is improved, the original data characteristics are better reserved, the distortion degree of the compressed compensation data is reduced, and the Demura compensation effect is further improved.

According to any of the foregoing embodiments of the first aspect of the present application, the target cluster number adjustment coefficients corresponding to at least some of the partitions are different.

Therefore, the compensation data of each partition can be compressed according to the corresponding target cluster quantity adjustment coefficient by flexibly adjusting the target cluster quantity adjustment coefficient corresponding to each partition according to the compensation data of different partitions, so that the compensation data of each partition has a larger compression ratio under the condition of meeting the compression precision requirement, and the compressed data quantity of each partition is reduced to a larger extent.

In a second aspect, an embodiment of the present application provides a data processing apparatus for a display panel, the display panel including a plurality of partitions, each partition including at least one subpixel, the data processing apparatus for the display panel including: the acquisition module is used for acquiring compensation data of a plurality of partitions; the first compression module is used for compressing the compensation data of the multiple partitions based on a target vector compression algorithm to obtain the compressed compensation data of the multiple partitions.

In a third aspect, embodiments of the present application provide a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the data processing method as provided in the first aspect.

The data processing method, the data processing device and the computer readable storage medium of the display panel acquire compensation data of a plurality of partitions in the display panel; and compressing the compensation data of the multiple partitions based on a target vector compression algorithm to obtain the compressed compensation data of the multiple partitions. According to the embodiment of the application, the target vector quantization algorithm is applied to compress the compensation data of a plurality of partitions, the compensation data of each partition can be classified and compressed according to the data size of the compensation data of each partition, the compression precision of the compensation data is improved, the characteristics of the original data are better reserved, the distortion degree of the compressed compensation data is reduced, and the Demura compensation effect is further improved.

Drawings

In order to more clearly illustrate the technical solution of the embodiments of the present application, the drawings that are needed to be used in the embodiments of the present application will be briefly described, and it is possible for a person skilled in the art to obtain other drawings according to these drawings without inventive effort.

Fig. 1 is a schematic flow chart of a data processing method of a display panel according to an embodiment of the present application;

fig. 2 is a schematic flow chart of another data processing method of a display panel according to an embodiment of the present application;

fig. 3 is a schematic flowchart of S203 in the data processing method of the display panel according to the embodiment of the present application;

fig. 4 is a schematic flow chart of a data processing method of a display panel according to an embodiment of the present application;

fig. 5 is a schematic flow chart of a data processing method of a display panel according to an embodiment of the present application;

fig. 6 is a flowchart of S202 in the data processing method of the display panel according to the embodiment of the present application;

fig. 7 is a schematic flowchart of S102 in the data processing method of the display panel according to the embodiment of the present application;

fig. 8 is a schematic flow chart of a data processing method of a display panel according to an embodiment of the present application;

FIG. 9 is a schematic diagram of a structure of a data processing apparatus of a display panel according to an embodiment of the present application;

fig. 10 shows a schematic hardware structure of an electronic device according to an embodiment of the present application.

Detailed Description

Features and exemplary embodiments of various aspects of the present application will be described in detail below, and in order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be described in further detail below with reference to the accompanying drawings and the detailed embodiments. It should be understood that the particular embodiments described herein are meant to be illustrative of the application only and not limiting. It will be apparent to one skilled in the art that the present application may be practiced without some of these specific details. The following description of the embodiments is merely intended to provide a better understanding of the application by showing examples of the application.

It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.

It should be understood that the term "and/or" as used herein is merely one relationship describing the association of the associated objects, meaning that there may be three relationships, e.g., a and/or B, may represent: a exists alone, A and B exist together, and B exists alone. In addition, the character "/" herein generally indicates that the front and rear associated objects are an "or" relationship.

It will be apparent to those skilled in the art that various modifications and variations can be made in the present application without departing from the spirit or scope of the application. Accordingly, it is intended that the present application covers the modifications and variations of this application provided they come within the scope of the appended claims (the claims) and their equivalents. The embodiments provided by the embodiments of the present application may be combined with each other without contradiction.

Before describing the technical solution provided by the embodiments of the present application, in order to facilitate understanding of the embodiments of the present application, the present application firstly specifically describes the problems existing in the related art:

the phenomenon of uneven brightness and chromaticity of the display panel can occur due to the influence of factors such as technology, materials, equipment and the like in the production process, and the phenomenon is called Mura. At present, the mainstream Demura method is mainly an external optical compensation method, namely, capturing brightness data of a display panel through a camera, calculating compensation data through a Demura algorithm, and writing the compensation data into a storage unit, so that brightness compensation of the display panel is realized.

Memory cells include, but are not limited to, static Random-Access Memory (SRAM). The storage capacity of the current storage unit (such as Demura SRAM) is about 16 megabits, but the data volume written into the storage unit is large due to the requirements of the number of shot gray scales and the compensation data depth. The compensation data needs to be compressed to meet the hardware resource requirements.

The inventor of the application discovers that the shooting gray scale number and the compensation data precision commonly influence the memory size and the compensation effect occupied by the data through long-term research. When the size of the occupied memory is fixed, the more the shooting gray scale is, the more accurate the calculation is, but the lower the corresponding compensation data depth (namely the data range) is, the phenomena of sandy feel, under-compensation or over-compensation are easy to occur after compensation. In contrast, if the number of shot gray scales is reduced and the depth of the compensation data is increased, the effect of shot gray scale compensation is good, but the effect of interpolation calculation gray scale compensation is poor. Therefore, the data compression plays a key role in the process, and the compensation data depth is kept as much as possible under the condition of keeping enough shooting gray scale, so as to achieve an optimal compensation effect.

However, long-term researches by the inventor of the present application have found that the compression method (such as the mean compression method) adopted at present can cause greater distortion of the compressed compensation data after the compensation data is compressed. If the compressed compensation data with large distortion is used for the demux compensation, the demux compensation effect is poor.

In view of the above-mentioned research of the inventor, the embodiments of the present application provide a data processing method and apparatus for a display panel, and a computer readable storage medium, which can solve the technical problem that the compensation effect of Demura is poor due to the fact that the compensation data in the related art is distorted greatly after data compression.

The technical conception of the embodiment of the application is as follows: and compressing the compensation data of the multiple partitions in the display panel based on a target vector compression algorithm to obtain the compressed compensation data of the multiple partitions, wherein 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, so that the compression precision of the compensation data is improved, the characteristics of the original data are better reserved, the distortion degree of the compressed compensation data is reduced, and the Demura compensation effect is further improved.

The following first describes a data processing method of a display panel provided by an embodiment of the present application.

In an embodiment of the present application, the display panel may include a plurality of partitions, and each partition may include at least one subpixel. It should be noted that, the number of the partitions in the display panel and the number of the sub-pixels in the partitions may be flexibly adjusted according to the actual situation, which is not limited in the embodiments of the present application, for example, in some examples, each partition may include 10×10 sub-pixels; each partition may also include 40 x 40 sub-pixels; preferably, the number of sub-pixels per partition may also lie between the two, i.e. (10-40) ×10-40 sub-pixels. In addition, the number of sub-pixels in different partitions may be the same or different, which is not limited in the embodiment of the present application.

Fig. 1 is a schematic flow chart of a data processing method of a display panel according to an embodiment of the application. As shown in fig. 1, the data processing method of the display panel may include the following steps S101 and S102.

S101, acquiring compensation data of a plurality of partitions.

The compensation data may 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 for each partition may include eachThe gray-scale compensation value of the sub-pixel in the partition, for example, h2=h1±Δh, where Δh represents the gray-scale compensation value of any i-th sub-pixel, H1 represents the gray-scale before the demux compensation of the i-th sub-pixel, H2 represents the gray-scale after the demux compensation of the i-th sub-pixel, and i is a positive integer. In other examples, the compensation data for each partition may include gray scale adjustment coefficients for the subpixels in each partition, e.g., h2=a (H1) ² +b×h1, where a and b represent gray scale adjustment coefficients of an arbitrary i-th sub-pixel, H1 represents gray scale before demux compensation of the i-th sub-pixel, H2 represents gray scale after demux compensation of the i-th sub-pixel, and i is a positive integer.

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

S102, compressing the compensation data of the multiple partitions based on a target vector compression algorithm to obtain the compressed compensation data of the multiple partitions.

Among them, the target vector quantization algorithm includes, but is not limited to, the LBG algorithm. The LBG algorithm is a vector quantization (Vector Quantization, VQ) design algorithm based on a training sequence, the number of center points is firstly set, then iteration is continuously circulated, the set threshold value is used as an iteration termination condition, and finally the value of the center points is obtained. The method has the advantages that through the data size, for example, a value with a smaller value can be classified into a class A, a value with a middle value is classified into a class B, a value with a larger value is classified into a class C, the three classes are only schematic, the larger the number of the center points is, the more classification is, and the higher the precision is after compression. The resulting distortion using vector quantization will be lower than usual scalar quantization.

In S102, the compensation data of the plurality of partitions may be compressed based on the target vector compression algorithm, to obtain the compressed compensation data of the plurality of partitions.

According to the data processing method of the display panel, compensation data of a plurality of subareas in the display panel are obtained; and compressing the compensation data of the multiple partitions based on a target vector compression algorithm to obtain the compressed compensation data of the multiple partitions. According to the embodiment of the application, the target vector quantization algorithm is applied to compress the compensation data of a plurality of partitions, the compensation data of each partition can be classified and compressed according to the data size of the compensation data of each partition, the compression precision of the compensation data is improved, the characteristics of the original data are better reserved, the distortion degree of the compressed compensation data is reduced, and the Demura compensation effect is further improved.

The inventors of the present application further realized that the compression accuracy and compression ratio of the target vector compression algorithm are affected by the cluster number adjustment coefficient (or number of splits) K. The larger the cluster number adjustment coefficient K, the higher the compression accuracy (i.e., the smaller the compression loss rate), and the smaller the compression ratio, the larger the amount of data after compression. The smaller the cluster number adjustment coefficient K, the lower the compression accuracy (i.e., the greater the compression loss rate), and the greater the compression ratio, the smaller the amount of data after compression. Therefore, it is necessary to balance between the compression accuracy and the compression ratio so that the compression ratio is large to reduce the amount of data after compression to a large extent in the case where the compensation data satisfies the compression accuracy requirement.

In view of this, for the compensation data of different partitions, the cluster number adjustment coefficients corresponding to each partition may be determined respectively, so that the compensation data of each partition can meet the compression precision requirement, and meanwhile, the compressed data amount is reduced to a greater extent.

Fig. 2 is a schematic flow chart of another data processing method of a display panel according to an embodiment of the application. As shown in fig. 2, optionally, before the step of compressing the compensation data of the plurality of partitions based on the target vector compression algorithm to obtain the compressed compensation data of the plurality of partitions in S102, the data processing method of the display panel may further include S201 to S203.

S201, compressing the compensation data of any partition based on a target vector compression algorithm of initial cluster quantity adjustment coefficients to obtain the compressed compensation data of the partition.

The initial cluster number adjustment coefficient, i.e., the initial value of the cluster number adjustment coefficient, may be set in advance. The size of the initial cluster number adjustment coefficient can be flexibly adjusted according to practical situations, and the embodiment of the application is not limited to the above. For example, in some examples, the initial cluster number adjustment coefficient may be 4, although the initial cluster number adjustment coefficient may be other values.

For the compensation data of any partition, the target vector compression algorithm of the coefficient can be adjusted based on the initial clustering quantity, and the compensation data of the partition can be compressed to obtain the compensation data after the partition is compressed.

S202, decompressing the compensation data after the partition compression to obtain the compensation data after the partition decompression.

In S202, the compressed compensation data of the partition may be decompressed, that is, restored, to obtain the decompressed compensation data of the partition.

S203, comparing the compensation data of the subarea before compression with the compensation data after decompression of the subarea, and determining a target cluster quantity adjustment coefficient according to a comparison result.

In S203, the compensation data of the partition before compression and the compensation data of the partition after decompression may be compared. For example, if the difference between the two is large, the current compression precision is not in accordance with the requirement, and the adjustment coefficient of the clustering quantity is required to be adjusted; if the difference between the two is smaller, the current compression precision meets the requirement, and the clustering 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 after decompression of the partition, the target cluster quantity adjustment coefficient adopted by the partition can be determined.

Correspondingly, S102, compressing the compensation data of the plurality of partitions based on the target vector compression algorithm to obtain the compressed compensation data of the plurality of partitions, which specifically may include:

and compressing the compensation data of the partition based on a target vector compression algorithm of the target cluster quantity adjustment coefficient to obtain the compensation data after the partition is compressed.

Specifically, after the target cluster number adjustment coefficient corresponding to each partition is obtained, for any ith partition, i is a positive integer, the cluster number adjustment coefficient of the target vector compression algorithm can be adjusted to be equal to the target cluster number adjustment coefficient corresponding to the ith partition, and then the compensation data of the ith partition is compressed, so that the compensation data of the ith partition after compression is obtained.

Fig. 3 is a flowchart of S203 in the data processing method of the display panel according to the embodiment of the application. As shown in fig. 3, according to some embodiments of the present application, optionally, S203, the step of comparing the compensation data of the partition before compression with the compensation data after decompression of the partition, and determining the target cluster number adjustment coefficient according to the comparison result may specifically include the following steps S301 and S302, and may further include at least one of S303 and S304.

S301, calculating the sum of absolute values of differences between compensation data before compression of a plurality of sub-pixels in the partition and compensation data after decompression of the plurality of sub-pixels in the partition.

A partition may include a plurality of subpixels. Accordingly, the compensation data before one partition compression may include compensation data before a plurality of sub-pixels in one partition, and the compensation data after one partition decompression may include compensation data after a plurality of sub-pixels in one partition are decompressed.

Taking a case where one partition includes N1 sub-pixels, N1 is an integer greater than 1, in S301, for any one partition, an absolute value of a difference between compensation data before compression of the 1 st sub-pixel in the partition and compensation data after decompression of the 1 st sub-pixel in the partition may be calculated, an absolute value of a difference between compensation data before compression of the 2 nd sub-pixel in the partition and compensation data after decompression of the 2 nd sub-pixel in the partition is calculated, … …, and an absolute value of a difference between compensation data before compression of the N1 st sub-pixel in the partition and compensation data after decompression of the N1 st sub-pixel in the partition is calculated. Then, the absolute values of the differences corresponding to the respective sub-pixels are added to obtain a sum of absolute values of differences between the compensation data before compression of the plurality of sub-pixels in the partition and the compensation data after decompression of the plurality of sub-pixels in the partition (hereinafter referred to as "sum").

S302, calculating the difference rate according to the number of the sub-pixels in the sum and the subarea.

Since the sum obtained in S301 will also 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 after decompression of the partition, the difference rate can be obtained from the sum obtained in 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 after decompression of the partition.

And S303, when the difference rate is greater than a preset threshold, increasing the clustering quantity adjusting coefficient until the difference rate is less than or equal to the preset threshold, and obtaining the target clustering quantity adjusting coefficient.

As described above, the larger the cluster number adjustment coefficient, the higher the compression accuracy. When the difference rate is larger than a preset threshold value, the fact that the currently adopted cluster quantity adjustment coefficient is smaller results in that the compression precision is not in accordance with the requirement is indicated. Therefore, when the difference rate is greater than the preset threshold, the cluster number adjustment coefficient may be increased until the difference rate is less than or equal to the preset threshold, thereby obtaining the target cluster number adjustment coefficient.

For example, when the difference rate is greater than a preset threshold, the cluster number adjustment coefficient may be increased according to a preset adjustment step, and then the initial cluster number adjustment coefficient is updated to the increased cluster number adjustment coefficient. For example, the original initial cluster number adjustment coefficient is 4, and the increased cluster number adjustment coefficient is 5, and the initial cluster number adjustment coefficient is changed from 4 to 5. Then, steps S201 to S203 are returned until the difference rate is less than or equal to the preset threshold. And finally, taking the corresponding cluster quantity adjusting coefficient when the difference rate is smaller than or equal to a preset threshold value as a target cluster quantity adjusting coefficient.

The magnitude of the preset threshold can be flexibly adjusted according to practical situations, and the embodiment of the application is not limited to the magnitude.

And S304, when the difference rate is smaller than a preset threshold, reducing the cluster quantity adjustment coefficient until the difference rate is larger than the preset threshold, and taking the last-time adjusted cluster quantity adjustment coefficient with the difference rate smaller than or equal to the preset threshold as a target cluster quantity adjustment coefficient.

Further long-term studies by the inventors of the present application have found that, in some cases, the compensation data of the partition is compressed, for example, based on the cluster number adjustment coefficient k=4, and although the requirement of compression accuracy can be satisfied, there may be a "waste" situation, that is, there is a situation that the subscript value (hereinafter, subscript value) is not used, and thus the data amount of the compressed compensation data is still larger.

In view of this, in S304, when the difference rate is smaller than the preset threshold, the cluster number adjustment coefficient may be reduced. And taking the last-time adjusted cluster quantity adjusting coefficient with the difference rate smaller than or equal to the preset threshold value as a target cluster quantity adjusting coefficient until the difference rate is larger than the preset threshold value.

For example, when the cluster number adjustment coefficient is 4, the difference rate is smaller than the preset threshold. When the cluster number adjustment coefficient is reduced to 3, the difference rate is still smaller than the preset threshold value. However, when the cluster number adjustment coefficient is reduced to 2, the difference rate is greater than the preset threshold. Then, the last-time adjusted cluster number adjustment coefficient with the difference rate smaller than or equal to the preset threshold value, such as 3, is used as the target cluster number adjustment coefficient. It should be noted that 2, 3, and 4 are only examples, and do not limit the present application.

In some specific embodiments, optionally, the sum of absolute values of differences between the compensation data before compression of the plurality of sub-pixels in the partition and the compensation data after decompression of the plurality of sub-pixels in the partition may be calculated according to the following expression:

In this way, by the above expression (1), the sum of absolute values of differences between the compensation data before the compression of the plurality of sub-pixels in the partition and the compensation data after the decompression of the plurality of sub-pixels in the partition can be obtained quickly and accurately.

In some specific embodiments, the rate of difference may optionally be calculated according to the following expression:

ratio＝100％*D/n (2)

For example, in some examples, a partition may include 20×20 subpixels, i.e., 400 subpixels, and accordingly, n may be equal to 400.

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

In some specific embodiments, the adjustment step of the cluster number adjustment coefficient may optionally include 1. That is, the step size of increasing the cluster number adjustment coefficient each time and/or decreasing the cluster number adjustment coefficient each time may be 1. When the adjustment step length of the cluster number adjustment coefficient is 1, for example, inaccuracy of the target cluster number adjustment coefficient which is finally adopted due to a large adjustment step length setting of the cluster number adjustment coefficient can be avoided, for example, overlong time spent in determining the target cluster number adjustment coefficient due to a small adjustment step length setting of the cluster number adjustment coefficient can be avoided.

The inventors of the present application further realized that the human eye is not equally sensitive to high gray levels and low gray levels. For example, at low gray levels, the front-to-back gray level changes by more than 10%, such as by ±1 gray level, and the human eye can feel the difference very sensitively. However, since the screen is brighter at high gray levels, the human eye is insensitive, and the front and rear gray levels change by more than 10%, for example, by ±3 gray levels, and the human eye may not find the difference. In view of this, different difference judging criteria may be used for the compensation data of different gray levels, for example, the preset threshold may be different for different gray levels.

Specifically, according to some embodiments of the present application, optionally, the compensation data of the plurality of partitions may include first compensation data of the plurality of partitions corresponding to a first target gray level and second compensation data of the plurality of partitions corresponding to a second target gray level, wherein the first target gray level is different from the second target gray level. The first target gray level and the second target gray level may be any gray levels, which is not limited in the embodiment of the present application. The preset threshold corresponding to the first target gray level is different from the preset threshold corresponding to the second target gray level.

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

Therefore, the target cluster quantity adjustment coefficients obtained under different gray scales can be different because the preset thresholds corresponding to different gray scales are different. Therefore, the compensation data with different gray scales can be compressed based on different target cluster quantity adjustment coefficients, so that the compensation data with different gray scales has a larger compression ratio under the condition that the compression precision requirement is met, and the compressed data quantity is reduced to a larger extent.

According to other embodiments of the present application, the difference ratio may alternatively be adjusted by using an adjustment coefficient related to the gray scale, for example, such that the difference ratio calculated by different gray scales is different.

In particular, the difference rate may be determined based on the number of subpixels in the accumulation, partition, and the adjustment factor. The adjustment coefficient corresponding to the first target gray level may be different from the adjustment coefficient corresponding to the second target gray level.

For example, in some specific embodiments, the rate of difference may be calculated according to the following expression:

ratio＝100％*D/n*p (3)

As can be seen from the above expression (3), the difference ratio is also affected by the adjustment coefficient p, for example, the larger the adjustment coefficient p is, the smaller the difference ratio is; the smaller the adjustment coefficient p, the larger the difference ratio. The adjustment coefficient p may be associated with a gray level, e.g., the adjustment coefficient corresponding to a first target gray level may be different from the adjustment coefficient corresponding to a second target gray level.

It should be noted that, when the adjustment coefficient corresponding to the first target gray level is different from the adjustment coefficient corresponding to the second target gray level, the preset threshold corresponding to the first target gray level may be the same as or different from the preset threshold corresponding to the second target gray level, which is not limited in the embodiment of the present application.

Thus, the adjustment coefficients corresponding to different gray scales are different, so that the adjustment coefficients of the target cluster number obtained under different gray scales can be different. Therefore, the compensation data with different gray scales can be compressed based on different target cluster quantity adjustment coefficients, so that the compensation data with different gray scales has a larger compression ratio under the condition that the compression precision requirement is met, and the compressed data quantity is reduced to a larger extent.

In some particular embodiments, the first target gray level may be less than the second target gray level. If the first target gray level is a lower gray level, the second target gray level is a higher gray level.

Accordingly, the preset threshold corresponding to the first target gray level may be smaller than the preset threshold corresponding to the second target gray level.

That is, when the gray level is higher, the judgment standard of the difference rate can be widened appropriately, so that a smaller cluster number adjustment coefficient is obtained, the compensation data is compressed as much as possible under the condition of meeting the compression precision requirement, and the data amount after compression is reduced to a greater extent.

In some embodiments, when the first target gray level is smaller than the second target gray level, the adjustment coefficient corresponding to the first target gray level may be smaller than the adjustment coefficient corresponding to the second target gray level.

As described above, the larger the adjustment coefficient p is, the smaller the difference ratio is; the smaller the adjustment coefficient p, the larger the difference ratio. Therefore, when the gray level is higher, the corresponding adjustment coefficient p is larger, the difference rate ratio can be reduced, and the compression precision requirement can be met under the condition that the adjustment coefficient of the clustering quantity is smaller.

For example, taking the adjustment coefficient p=1 corresponding to the first target gray level and the adjustment coefficient p=2 corresponding to the second target gray level as an example, when p=1, ratio=100% D/n, and 100% D/n is greater than the preset threshold, as shown in the above expression (3), the cluster number adjustment coefficient needs to be increased. When p=2, ratio=100%/n×2, and only when the sum D increases to 2D, 100%/n× 2*D/n×2 is equal to 100%/D/n, that is, the number of clusters adjustment coefficient needs to be increased when the sum D increases to 2D, so that a smaller number of clusters adjustment coefficient can be used, so that the compensation data is compressed as much as possible under the condition of meeting the compression precision requirement, and the compressed data amount is reduced to a greater extent.

The compression process for the target vector quantization algorithm is described in detail below.

Fig. 4 is a schematic flow chart of a data processing method of a display panel according to an embodiment of the application. As shown in fig. 4, according to some embodiments of the present application, optionally, the compensation data of the partition is compressed based on a target vector compression algorithm of the target cluster number adjustment coefficient, so as to obtain the compensation data after the partition is compressed, which may specifically include the following steps S401 and S402.

S401, dividing compensation data of a plurality of sub-pixels in a partition in a target gray level into N sections for any one partition, and determining a central value of each section according to the compensation data of the sub-pixels in the target gray level contained in each section.

The target gray level is any gray level binding point, for example, the target gray level may be 16 gray levels, 64 gray levels, 192 gray levels or other gray levels. N=2 ^K K is a target cluster quantity adjustment coefficient, and K and N are positive integers. Thereby can be used forIt is seen that the number of intervals or the number of center values is affected by the target cluster number adjustment coefficient K, for example, when the target cluster number adjustment coefficient k=4, n=2 ⁴ =16, namely dividing the compensation data of the plurality of sub-pixels in one partition at the target gray level into 16 intervals, to obtain 16 center values.

Taking an example that one partition includes 20×20 pixels, that is, 400 pixels, the compensation data of 400 pixels in the partition at the target gray level may be divided into N intervals (or called areas) according to the size of the compensation data. The compensation data for all sub-pixels in each interval at the target gray level may be replaced with the same center value, i.e. one interval corresponds to one center value. The embodiment of the application is not limited to the way of calculating the center value, and for example, the center value can be calculated by adopting the way of calculating the center value by adopting the LBG algorithm which is commonly adopted at present. For example, in some examples, for any one section, the average value, median, or mode of the compensation data for the sub-pixels included in the section at the target gray level may be calculated, and the average value, median, or mode of the compensation data for the sub-pixels included in the section at the target gray level may be taken as the center value of the section.

S402, generating a lower index value corresponding to any sub-pixel in the subarea according to the section to which the compensation data of the sub-pixel belongs.

In S402, the interval to which the compensation data of each sub-pixel belongs is known. Different sections may correspond to different subscript values, for example, section a corresponds to subscript value a1, section B corresponds to subscript value B1, and section C corresponds to subscript value C1. The function of the lower index value is to accurately determine the interval to which the sub-pixel belongs and the corresponding center value according to the lower index value corresponding to the sub-pixel after the lower index value is given to the sub-pixel. For example, when the subscript value corresponding to a subpixel is B1, it can be known that the subpixel belongs to the B interval, and the center value corresponding to the subpixel is the center value of the B interval, so that the subsequent decompression is convenient.

For any one partition, the compensation data after the partition compression comprises a central value of each interval and a lower index value corresponding to each sub-pixel in the partition.

Accordingly, the data processing method of the display panel may further include the following step S403.

S403, for any one partition, storing the central value of each interval in the partition and the index value corresponding to each sub-pixel in the partition into a storage unit.

For any one partition, the center value of each interval in the partition and the index value corresponding to each sub-pixel in the partition are stored in a storage unit.

It should be noted that, when the target vector compression algorithm compresses the compensation data of the partition by using the initial cluster number adjustment coefficient, the process is similar to the above steps S401 and S402, and will not be repeated here.

In some specific examples, one partition may include multiple color subpixels, such as a red subpixel, a green subpixel, and a blue subpixel. Accordingly, S401 may specifically include the following steps:

for any ith color sub-pixel in the partition, dividing compensation data of a plurality of ith color sub-pixels in the partition when the target gray level is reached into N sections, and determining the central value of the ith color sub-pixel in each section according to the compensation data of the ith color sub-pixel in each section when the target gray level is reached, wherein i is a positive integer, and i is more than or equal to 1 and less than or equal to N. N=2 ^K K is a target cluster quantity adjustment coefficient, and K and N are positive integers.

In S401, for any one of the partitions, for example, the compensation data of the plurality of red sub-pixels in the partition at the target gray level may be divided into N sections, and the center value corresponding to the red sub-pixel in each section may be determined according to the compensation data of the red sub-pixel included in each section at the target gray level. The compensation data of the plurality of green sub-pixels in the partition at the target gray level can be divided into N sections, and the central value corresponding to the green sub-pixels in each section is determined according to the compensation data of the green sub-pixels in each section at the target gray level. The compensation data of the plurality of blue sub-pixels in the partition at the target gray level can be divided into N sections, and the central value corresponding to the blue sub-pixels in each section is determined according to the compensation data of the blue sub-pixels in each section at the target gray level.

Correspondingly, S402, for any one sub-pixel in the partition, generating a subscript value corresponding to the sub-pixel according to the interval to which the compensation data of the sub-pixel belongs, which specifically includes the following steps:

for any ith color sub-pixel in the partition, generating a lower index value corresponding to the ith color sub-pixel according to the section to which the compensation data of the ith color sub-pixel belongs.

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 subpixel, a subscript value corresponding to the red subpixel may be generated according to the interval to which the compensation data for the red subpixel belongs. For each green sub-pixel, a subscript value corresponding to the green sub-pixel may be generated according to a section 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 may be generated based on a section to which the compensation data for the blue sub-pixel belongs.

Fig. 5 is a schematic flow chart of a data processing method of a display panel according to an embodiment of the application. As shown in fig. 5, optionally, before storing the center value of each section in a section and the index value corresponding to each sub-pixel in the section in the storage unit for any one section in S403, the data processing method of the display panel may further include the following steps S501 and/or S502.

S501, limiting the number of bits of the central value from the first number of bits to a second number of bits, wherein the second number of bits is smaller than the first number of bits.

For example, in some examples, the first number of bits may be an 8-bit number and the second number of bits may be less than 8-bit number, such as a 4-bit number or a 5-bit number, or the like. When the center value (or the compensation data) is 8-bit, the data range of the center value (or the compensation data) is large. When the bit limit of the central value is limited to 4 bits or 5 bits, the data range of the central value is reduced, and the data volume of the central value is reduced, so that the data volume of the central value is further reduced, and the storage cost of the storage unit is further reduced.

For example, in some embodiments, the second number of bits may be 4 bits, the most significant bit is a sign bit, and the sign is ±, such as±0000 to±1111, i.e. the gray level compensation interval is ±15, and the out-of-range overflow is direct. For example, in some specific embodiments, the second number may be a 5-bit number, the most significant bit is a sign bit, and the sign is ±, for example ±00000 to ±11111, that is, the gray level compensation interval is ±31, and the out-of-range overflow is direct.

S502, limiting the bit number of the subscript value to a third bit number, wherein the third bit number is smaller than the first bit number.

Similarly, the number of bits of the subscript value may be limited to be less than the first number of bits, such as 4 bits or 5 bits. When the bit limit of the lower marker value is limited to 4 bits or 5 bits, the data range of the lower marker value is reduced, and then the data volume of the lower marker value is also reduced, so that the data volume of the lower marker value is further reduced, and the storage cost of the storage unit is further reduced.

In some examples, the original number of bits (or starting number of bits) of the subscript value may be the first number of bits, i.e., the number of bits of the subscript value may be limited from the first number of bits to be less than the first number of bits. In other examples, the original number of bits (or starting number of bits) of the subscript may be greater than the first number of bits, i.e., the number of bits of the subscript may be limited from greater than the first number of bits to less than the first number of bits. In still other examples, the number of bits of the subscript may be limited to be less than the first number of bits directly when generating the subscript, which is not limited by the embodiment of the present application.

For example, in some embodiments, the third digit may be a 4-digit number, the most significant digit being the sign digit, the sign being ±, such as±0000 to ±1111, i.e., ±15, and the out of range overflows directly. For example, in some specific embodiments, the third digit may be a 5-digit number, the most significant digit being the sign digit, the sign being ±, such as±00000 to±11111, i.e., ±31, and the out of range directly overflows.

The following description will take an example in which the number of bits of the subscript is 4, n=16.

Table 1 schematically shows the central values of the 16 sections and the subscript values corresponding to the respective central values.

TABLE 1

As shown in table 1, in some examples, for example, compensation data of a plurality of sub-pixels in each partition at a target gray scale binding point may be divided into 16 sections, and a to Q represent center values of the 16 sections, respectively. Each center value may correspond to a subscript value (or label value). For example, the center value a corresponds to the subscript value 0, the center value B corresponds to the subscript value 1, … …, and the center value Q corresponds to the subscript value 15. Each sub-pixel in a partition may be assigned a subscript value, e.g., 20 x 20 pixels in a partition may be assigned 400 subscript values, and the set of subscript values may be denoted index. The set of center values may be denoted as value.

Correspondingly, for any one partition, S403, the center value of each interval in the partition and the subscript value corresponding to each sub-pixel in the partition are stored in the storage unit, which specifically may include the following steps:

and storing the central value after limiting the bit number of each interval in the partition and/or the subscript value after limiting the bit number of each sub-pixel in the partition into a storage unit.

Specifically, the center value after the limitation of the number of bits of each section in the partition and the lower index value after the limitation of the number of bits of each sub-pixel in the partition may be stored in the storage unit. Or, the center value after the limitation of the bit number of each section in the partition and the subscript value corresponding to each sub-pixel in the partition are stored in the storage unit. Alternatively, the center value of each section in the partition and the subscript value of each sub-pixel bit number in the partition after the restriction are stored in the storage unit.

That is, at least one of the center value and the subscript value may be subjected to a bit number limitation, which is not limited by the embodiment of the present application.

In some particular embodiments, the third number of bits may be less than the second number of bits. For example, the number of bits of the center value may be limited to 5-bit numbers, and the number of bits of the subscript value may be limited to 4-bit numbers. Therefore, the data range of the lower standard value can be reduced to a large extent, the data volume of the lower standard value is further reduced, the storage space is saved, and the storage cost is reduced.

Fig. 6 is a flowchart of S202 in the data processing method of the display panel according to the embodiment of the application. As shown in fig. 6, according to some embodiments of the present application, optionally, step S202 of decompressing the compensated data after the partition compression to obtain the compensated data after the partition decompression may specifically include the following steps S601 and S602.

S601, for any sub-pixel in the subarea, determining a corresponding central value of the sub-pixel in the target gray level according to the corresponding relation between the lower standard value and the central value in the target gray level and the lower standard value of the sub-pixel.

As described above, different center values (or sections) may correspond to different lower index values, and as shown in table 1, a correspondence relationship between the lower index value and the center value at the time of the target gray level may be established in advance. For any sub-pixel in the subarea, the corresponding central value of the sub-pixel in the target gray level can be determined according to the decompressed lower standard value of the sub-pixel and the corresponding relation between the lower standard value and the central value in the target gray level.

S602, taking the central value corresponding to the sub-pixel as compensation data of the sub-pixel in the target gray scale.

For any one sub-pixel in the subarea, after the central value corresponding to the sub-pixel in the target gray level is obtained, the central value corresponding to the sub-pixel can be used as compensation data of the sub-pixel in the target gray level. The compensation data can be used for correcting the gray scale to be displayed of the sub-pixel, so as to realize Demura compensation.

Fig. 7 is a flowchart of S102 in the data processing method of the display panel according to the embodiment of the present application. As shown in fig. 7, according to some embodiments of the present application, optionally, S102, the step of compressing the compensation data of the plurality of partitions based on the target vector compression algorithm to obtain the compressed compensation data of the plurality of partitions may specifically include the following steps S701 to S703.

S701, for any one partition, determining background data corresponding to the partition according to gray scales displayed by the partition.

In some examples, the background data includes, but is not limited to, gray levels that the partition desires to display. For example, for compensation data for a partition at a target gray level, the background data may be the target gray level. Taking the example that the gray scale desired to be displayed by the partition (i.e., the target gray scale) is 32 gray scales, the background data may be 32 gray scales.

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

That is, the background data is subtracted from the compensation data of the partition, thereby obtaining the compensation data of the partition from which the background data is removed.

When the number of bits of the compensation data is different from that of the background data, the number of bits of the background data is converted to be the same as that of the compensation data, and then the calculation is performed. Taking 129 as the compensation data of one sub-pixel of the partition, 32 gray scales as an example of the background data, 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 into 10 bits, that is, 32×4=128. And then 129-128=1 is utilized, so that the compensation data of the sub-pixel after background data is removed is obtained.

S703, compressing the compensation data after removing the background data from the partition based on a target vector compression algorithm to obtain the compensation data after compressing the partition.

In S703, the compensation data after the background data is removed from the partition may 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 is described in detail above and will not be described in detail here.

Fig. 8 is a schematic flow chart of a data processing method of a display panel according to an embodiment of the application. As shown in fig. 8, optionally, before the step of compressing the compensation data after the background data is removed from the partition based on the target vector compression algorithm in S703 to obtain the compensation data after the partition compression, the data processing method of the display panel may further include the following step S801.

S801, based on a block compression algorithm, carrying out mean compression on the compensation data after the background data is removed from the partition, and obtaining the compensation data after the partition mean compression.

The Block compression is also called Block compression, and may select blocks (compression ratio) of 1*1, 1*2, 2*1 or 2×2, etc. to perform average compression on the luminance compensation data according to the compression requirement. For example, for a set of 2 rows and 4 columns of dataPerforming block1 x 2 compression to obtain a mean value of every row and every two columns to obtain +.>Becomes 2 rows and 2 columns.

Correspondingly, S703, compressing the compensation data after removing the background data from the partition based on the target vector compression algorithm, to obtain the compensation data after compressing the partition, which specifically may include the following steps:

and compressing the compensation data after the partition mean value compression based on a target vector compression algorithm to obtain the compensation data after the partition compression.

That is, the compensation data may be first block-compressed, and then vector-quantized and compressed, so that the method is applicable to a case where the compression ratio is high.

According to some embodiments of the application, the cluster number adjustment coefficients corresponding to at least some of the partitions may optionally be different.

Based on the data processing method of the display panel provided by the embodiment, correspondingly, the application further provides a specific implementation mode of the data processing device of the display panel. Please refer to the following examples.

Fig. 9 is a schematic structural diagram of a data processing device of a display panel according to an embodiment of the present application. As shown in fig. 9, a data processing apparatus 90 of a display panel according to an embodiment of the present application includes the following modules:

an acquisition module 901, configured to acquire compensation data of a plurality of partitions;

the first compression module 902 is configured to compress the compensation data of the plurality of partitions based on the target vector compression algorithm, to obtain the compressed compensation data of the plurality of partitions.

The data processing device of the display panel acquires compensation data of a plurality of partitions in the display panel; and compressing the compensation data of the multiple partitions based on a target vector compression algorithm to obtain the compressed compensation data of the multiple partitions. According to the embodiment of the application, the target vector quantization algorithm is applied to compress the compensation data of a plurality of partitions, the compensation data of each partition can be classified and compressed according to the data size of the compensation data of each partition, the compression precision of the compensation data is improved, the characteristics of the original data are better reserved, the distortion degree of the compressed compensation data is reduced, and the Demura compensation effect is further improved.

In some embodiments, the data processing apparatus 90 of a display panel provided by the embodiments of the present application further includes a determining module, configured to compress, for compensation data of any one partition, the compensation data of the partition based on a target vector compression algorithm of an initial cluster number adjustment coefficient, to obtain the compensation data after the partition is compressed; decompressing the compensation data after the partition compression to obtain the compensation data after the partition decompression; comparing the compensation data of the subarea before compression with the compensation data after decompression of the subarea, and determining a target cluster quantity adjustment coefficient according to a comparison result. The first compression module 902 is specifically configured to compress the compensation data of the partition based on a target vector compression algorithm of a target cluster number adjustment coefficient, so as to obtain the compensation data after the partition is compressed.

In some embodiments, the determining module is specifically configured to calculate a sum of absolute values of differences between compensation data before compression of the plurality of sub-pixels in the partition and compensation data after decompression of the plurality of sub-pixels in the partition; calculating a difference rate according to the number of sub-pixels in the sum and the partition; when the difference rate is larger than a preset threshold, increasing the clustering quantity adjusting coefficient until the difference rate is smaller than or equal to the preset threshold, and obtaining a target clustering quantity adjusting coefficient; and/or when the difference rate is smaller than a preset threshold, reducing the cluster number adjustment coefficient until the difference rate is larger than the preset threshold, and taking the last-time adjusted cluster number adjustment coefficient with the difference rate smaller than or equal to the preset threshold as the target cluster number adjustment coefficient.

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

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

ratio＝100％*D/n

In some embodiments, the adjustment step of the cluster number adjustment coefficient includes 1.

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

ratio＝100％*D/n*p

In some embodiments, the first target gray level is less than the second target gray level; the preset threshold value corresponding to the first target gray level is smaller than the preset threshold value corresponding to the second target gray level, and/or the adjustment coefficient corresponding to the first target gray level is smaller than the adjustment coefficient corresponding to the second target gray level.

In some embodiments, the first compression module 902 is specifically configured to divide, for any one partition, compensation data of a plurality of sub-pixels in the partition at a target gray level into N intervals, and determine a center value of each interval according to the compensation data of the sub-pixels included in each interval at the target gray level, where the target gray level is any one gray level binding point, and n=2 ^K K is a target cluster quantity adjustment coefficient, and K and N are positive integers; for any one sub-pixel in the partition, generating a lower index value corresponding to the sub-pixel according to the section to which the compensation data of the sub-pixel belongs. The compensation data after the partition compression comprises a central value of each interval and a lower index value corresponding to each sub-pixel in the partition. The data processing device 90 of the display panel provided in the embodiment of the present application further includes a storage module, configured to store, for any one partition, a center value of each section in the partition and a subscript value corresponding to each sub-pixel in the partition into a storage unit.

In some embodiments, the data processing apparatus 90 of a display panel provided by the embodiments of the present application further includes a limiting module, configured to limit the number of bits of the center value from a first number of bits to a second number of bits, where the second number of bits is smaller 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. The storage module is specifically configured to store the center value after the bit number of each section in the partition is limited and/or the subscript value after the bit number of each sub-pixel in the partition is limited into the storage unit.

In some embodiments, the determining module is specifically configured to determine, for any one of the sub-pixels in the partition, a center value corresponding to the sub-pixel in the target gray level according to a correspondence between the center value and the lower index value of the sub-pixel in the target gray level; and taking the central value corresponding to the sub-pixel as compensation data of the sub-pixel in the target gray scale.

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

In some embodiments, the data processing apparatus 90 of a display panel according to the present application further includes a second compression module, configured to perform mean compression on the compensation data after the background data is removed from the partition based on a block compression algorithm, to obtain the compensation data after the partition mean compression. The first compression module 902 is specifically configured to compress the partition mean compressed compensation data based on a target vector compression algorithm, to obtain the partition compressed compensation data.

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

In some embodiments, the target cluster number adjustment coefficients corresponding to at least some of the partitions are different.

Each module/unit in the data processing apparatus of the display panel shown in fig. 9 has a function of implementing each step in the data processing method of the display panel provided in the foregoing method embodiment, and can achieve a corresponding technical effect, which is not described herein for brevity.

Based on the data processing method of the display panel provided by the embodiment, correspondingly, the application further provides a specific implementation mode of the electronic equipment. Please refer to the following examples.

The electronic device may include a processor 1001 and a memory 1002 storing computer program instructions.

In particular, the processor 1001 described above may include a central processing unit (Central Processing Unit, CPU), or an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), or may be configured as one or more integrated circuits implementing embodiments of the present application.

Memory 1002 may include mass storage for data or instructions. By way of example, and not limitation, memory 1002 may include a Hard Disk Drive (HDD), floppy Disk Drive, flash memory, optical Disk, magneto-optical Disk, magnetic tape, or universal serial bus (Universal Serial Bus, USB) Drive, or a combination of two or more of the foregoing. In one example, the memory 1002 may include removable or non-removable (or fixed) media, or the memory 1002 is a non-volatile solid state memory. The memory 1002 may be internal or external to the electronic device.

In one example, memory 1002 may be Read Only Memory (ROM). In one example, the ROM may be mask-programmed ROM, programmable ROM (PROM), erasable PROM (EPROM), electrically Erasable PROM (EEPROM), electrically rewritable ROM (EAROM), or flash memory, or a combination of two or more of these.

Memory 1002 may include Read Only Memory (ROM), random Access Memory (RAM), magnetic disk storage media devices, optical storage media devices, flash memory devices, electrical, optical, or other physical/tangible memory storage devices. Thus, in general, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software comprising computer-executable instructions and when the software is executed (e.g., by one or more processors) it is operable to perform the operations described with reference to a method in accordance with an aspect of the application.

The processor 1001 reads and executes the computer program instructions stored in the memory 1002 to implement the methods/steps in the above-mentioned method embodiments, and achieve the corresponding technical effects achieved by the method embodiments executing the methods/steps, which are not described herein for brevity.

In one example, the electronic device may also include a communication interface 1003 and a bus 1010. As shown in fig. 10, the processor 1001, the memory 1002, and the communication interface 1003 are connected to each other by a bus 1010, and perform communication with each other.

The communication interface 1003 is mainly used for implementing communication among the modules, devices, units and/or apparatuses in the embodiment of the application.

Bus 1010 includes hardware, software, or both, coupling components of an electronic device to each other. By way of example, and not limitation, the buses may include an accelerated graphics port (Accelerated Graphics Port, AGP) or other graphics Bus, an enhanced industry standard architecture (Extended Industry Standard Architecture, EISA) Bus, a Front Side Bus (FSB), a HyperTransport (HT) interconnect, an industry standard architecture (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 other suitable Bus, or a combination of two or more of the above. Bus 1010 may include one or more buses, where appropriate. Although embodiments of the application have been described and illustrated with respect to a particular bus, the application contemplates any suitable bus or interconnect.

In addition, in combination with the data processing method of the display panel in the above embodiment, the embodiment of the application may be implemented by providing a computer readable storage medium. The computer readable storage medium has stored thereon computer program instructions; the computer program instructions, when executed by a processor, implement a data processing method for any of the display panels of the above embodiments. Examples of computer readable storage media include non-transitory computer readable storage media such as electronic circuits, semiconductor memory devices, ROMs, random access memories, flash memories, erasable ROMs (EROM), floppy disks, CD-ROMs, optical disks, hard disks.

It should be understood that the application is not limited to the particular arrangements and instrumentality described above and shown in the drawings. For the sake of brevity, a detailed description of known methods is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method processes of the present application are not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between steps, after appreciating the spirit of the present application.

The functional blocks shown in the above-described structural block diagrams may be implemented in hardware, software, firmware, or a combination thereof. When implemented in hardware, it may be, for example, an electronic circuit, an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), suitable firmware, a plug-in, a function card, or the like. When implemented in software, the elements of the application are the programs or code segments used to perform the required tasks. The program or code segments may be stored in a machine readable medium or transmitted over transmission media or communication links by a data signal carried in a carrier wave. A "machine-readable medium" may include any medium that can store or transfer information. Examples of machine-readable media include electronic circuitry, 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 may be downloaded via computer networks such as the internet, intranets, etc.

It should also be noted that the exemplary embodiments mentioned in this disclosure describe some methods or systems based on a series of steps or devices. However, the present application is not limited to the order of the above-described steps, that is, the steps may be performed in the order mentioned in the embodiments, or may be performed in a different order from the order in the embodiments, or several steps may be performed simultaneously.

Aspects of the present application are described above with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions/acts specified in the flowchart and/or block diagram block or blocks. Such a processor may be, but is not limited to being, a general purpose processor, a special purpose processor, an application specific processor, or a field programmable logic circuit. It will also be understood that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware which performs the specified functions or acts, or combinations of special purpose hardware and computer instructions.

In the foregoing, only the specific embodiments of the present application are described, and it will be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the systems, modules and units described above may refer to the corresponding processes in the foregoing method embodiments, which are not repeated herein. It should be understood that the scope of the present application is not limited thereto, and any equivalent modifications or substitutions can be easily made by those skilled in the art within the technical scope of the present application, and they should be included in the scope of the present application.

Claims

1. A data processing method of a display panel, wherein the display panel comprises a plurality of partitions, each of the partitions comprising at least one subpixel, the method comprising:

acquiring compensation data of the plurality of partitions;

and compressing the compensation data of the plurality of partitions based on a target vector compression algorithm to obtain the compressed compensation data of the plurality of partitions.

2. The method of claim 1, wherein prior to the step of compressing the compensation data for the plurality of partitions based on the target vector compression algorithm to obtain the compressed compensation data for the plurality of partitions, the method further comprises:

For the compensation data of any partition, compressing the compensation data of the partition based on the target vector compression algorithm of the initial clustering quantity adjustment coefficient to obtain the compressed compensation data of the partition;

decompressing the compensation data after the partition compression to obtain the compensation data after the partition decompression;

comparing the compensation data of the subarea before compression with the compensation data of the subarea after decompression, 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 the compressed compensation data of the plurality of partitions specifically includes:

and compressing the compensation data of the partition based on the target vector compression algorithm of the target cluster quantity adjustment coefficient to obtain the compressed compensation data of the partition.

3. The method according to claim 2, wherein 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 number adjustment coefficient according to the comparison result, specifically comprises:

Calculating the sum of absolute values of differences between compensation data before compression of a plurality of sub-pixels in the partition and compensation data after decompression of the plurality of sub-pixels in the partition;

calculating a difference rate according to the sum and the number of sub-pixels in the partition;

when the difference rate is larger than a preset threshold, increasing a clustering quantity adjusting coefficient until the difference rate is smaller than or equal to the preset threshold, and obtaining the target clustering quantity adjusting coefficient;

and/or, when the difference rate is smaller than a preset threshold, reducing a cluster number adjustment coefficient until the difference rate is larger than the preset threshold, and taking the last-time adjusted cluster number adjustment coefficient with the difference rate smaller than or equal to the preset threshold as the target cluster number adjustment coefficient;

preferably, the sum of absolute values of differences between the compensation data before compression of the plurality of sub-pixels in the partition and the compensation data after decompression of the plurality of sub-pixels in the partition is calculated according to the following expression:

wherein D represents the summation, dataS (k) represents the compensation data before the compression of the kth sub-pixel in the partition, dataD (k) represents the compensation data after the decompression of the kth sub-pixel in the partition, n represents the number of sub-pixels in the partition, abs represents absolute value operation, k and n are positive integers, and k is more than or equal to 1 and less than or equal to n;

Preferably, 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;

preferably, the adjustment step size of the cluster number adjustment coefficient includes 1.

4. The method of claim 3, wherein the compensation data for the plurality of partitions includes first compensation data for the plurality of partitions at a first target gray level and second compensation data for the plurality of partitions at a second target gray level, the first target gray level being different from the second target gray level;

the preset threshold corresponding to the first target gray level is different from the preset threshold corresponding to the second target gray level;

and/or, the difference rate is determined according to the sum, the number of sub-pixels in the partition and an adjustment coefficient, wherein the adjustment coefficient corresponding to the first target gray scale is different from the adjustment coefficient corresponding to the second target gray scale;

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 is greater than or equal to 1, and n is a positive integer.

5. The method of claim 4, wherein the first target gray level is less than the second target gray level;

the preset threshold corresponding to the first target gray level is smaller than the preset threshold corresponding to the second target gray level, and/or the adjustment coefficient corresponding to the first target gray level is smaller than the adjustment coefficient corresponding to the second target gray level.

6. The method according to any one of claims 2 to 5, wherein the step of compressing the compensation data of the partition by the target vector compression algorithm based on the target cluster number adjustment coefficient to obtain the compressed compensation data of the partition specifically includes:

for any one of the partitions, dividing the compensation data of the plurality of sub-pixels in the partition in the target gray scale into N sections, and determining the central value of each section according to the compensation data of the sub-pixels in the target gray scale contained in each section, wherein the target gray scale is any one of the gray scale binding points, 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 subarea, generating a lower index value corresponding to the sub-pixel according to the interval to which the compensation data of the sub-pixel belongs;

The compensation data after the partition compression comprises a central value of each interval and a lower standard value corresponding to each sub-pixel in the partition;

the method further comprises the steps of:

for any one of the partitions, storing a center value of each section in the partition and a subscript value corresponding to each sub-pixel in the partition into a storage unit;

preferably, before the step of storing the center value of each section in the partition and the index value corresponding to each sub-pixel in the partition in the storage unit, the method further includes:

limiting the number of bits of the central value from a first number of bits 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;

the step of storing the center value of each section in the partition and the subscript value corresponding to each sub-pixel in the partition in a storage unit specifically includes:

and storing the central value after limiting the bit number of each interval in the partition and/or the subscript value after limiting the bit number of each sub-pixel in the partition into the storage unit.

7. The method according to claim 6, wherein the step of decompressing the partition compressed compensation data to obtain the partition decompressed compensation data specifically comprises:

for any one sub-pixel in the subarea, determining a corresponding central value of the sub-pixel in the target gray level according to the corresponding relation between the lower standard value and the central value in the target gray level and the lower standard value of the sub-pixel;

and taking the central value corresponding to the sub-pixel as compensation data of the sub-pixel in the target gray scale.

8. The method according to claim 1, wherein the step of compressing the compensation data of the plurality of partitions based on the target vector compression algorithm to obtain the compressed compensation data of the plurality of partitions specifically comprises:

for any one of the partitions, determining background data corresponding to the partition according to gray scales displayed by the partition;

removing the background data from the compensation data of the partition to obtain the compensation data of the partition from which the background data is removed;

compressing the compensation data of the partition after removing the background data based on the target vector compression algorithm to obtain the compensation data of the partition after compression;

Preferably, before the step of compressing the compensation data of the partition after removing the background data based on the target vector compression algorithm to obtain the compensation data of the partition after compression, the method further includes:

based on a block compression algorithm, carrying out mean compression on the compensation data of the partition after removing the background data to obtain the compensation data of the partition after mean compression;

the step of compressing the compensation data of the partition after removing the background data based on the target vector compression algorithm to obtain the compensation data of the partition after compressing specifically includes:

and compressing the compensation data after the partition mean value compression based on the target vector compression algorithm to obtain the compensation data after the partition compression.

9. The method according to any of claims 1-8, wherein the target vector compression algorithm comprises an LBG algorithm;

preferably, at least part of target cluster quantity adjustment coefficients corresponding to the partitions are different.

10. A data processing apparatus of a display panel, the display panel comprising a plurality of partitions, each of the partitions comprising at least one subpixel, the apparatus comprising:

The acquisition module is used for acquiring the compensation data of the plurality of partitions;

the first compression module is used for compressing the compensation data of the plurality of partitions based on a target vector compression algorithm to obtain the compressed compensation data of the plurality of partitions.

11. A computer-readable storage medium, on which a computer program is stored, which computer program, when being executed by a processor, implements the steps of the data processing method of a display panel according to any one of claims 1 to 9.