WO2020082632A1

WO2020082632A1 - Method for processing image data

Info

Publication number: WO2020082632A1
Application number: PCT/CN2019/072496
Authority: WO
Inventors: 关晓亮
Original assignee: 深圳市华星光电技术有限公司
Priority date: 2018-10-26
Filing date: 2019-01-21
Publication date: 2020-04-30
Also published as: CN109640065A

Abstract

The method in the present disclosure comprises: obtaining pixels of each row of an image, and comparing R, G, and B values of the pixels by means of an algorithm; configuring a discard value, and comparing the quantity of pixels in a clock cycle with the discard value; configuring a discard condition value, and obtaining, for new pixels, RGB grayscale values and the quantity of the new pixels; upon completing processing, performing a matrix operation with respect to the RGB grayscale values and the pixel quantity, and obtaining new mutually consistent RGB values and recording the quantity of corresponding pixels; and performing processing on a column so as to achieve processing of all data.

Description

Method for processing picture data

Technical field

The present disclosure relates to the field of display technology, and in particular, to a method for processing picture data.

Background technique

With the continuous development of optoelectronics and semiconductor technology, it has also led to progress in display devices and other fields. The processing technology of the display screen image by related components in the display device further reflects the display effect of the display.

The colors to be expressed on the display screen are becoming richer and richer, and also more delicate, especially for Ultra High Definition (UD), these are derived from the increase of full-screen information data. The same display frame contains The amount of information is even greater. At present, there are more and more calculation technologies for display screen processing, and the storage space occupied by full-screen information storage is also very large. For example, in the UD screen, the amount of data in one frame of data is 3840 * 2160 * 2 ⁸ * 2 ⁸ * 2 ⁸ , the total number of pixels of the entire display device reaches more than 8 million, and the amount of data information is particularly large. When these data frames are processed, the ratio of data compression will be large, and the maximum amount of data and the RGB gray scale value of the same data cannot be quickly found from the same frame. In the existing compression technology, the compression ratio The larger the picture, the more the picture is distorted, and the picture processing of the color cast is not ideal, which reduces the display effect of the ultra-high-strength screen. At the same time, when comparing the same frame of data, the amount of data cannot be completed .

technical problem

Therefore, the existing technology cannot quickly find the maximum value of the same amount of data and its RGB grayscale value from the same frame when processing more full-screen data and compressed data, which has low accuracy and limits the ultra-high-strength and other screens. To show the effect, further improvement and improvement plans need to be proposed.

Technical solution

The present disclosure provides a method for processing image data to solve the problem that the prior art cannot quickly find the maximum amount of the same amount of data and its RGB grayscale value from the same frame when processing more full-screen data and compressing data. The problem of low accuracy.

To solve the above technical problems, the technical solutions provided by the present disclosure are as follows:

According to the first embodiment of the disclosed embodiments, a method for processing picture data is provided, including the following steps:

S100. Acquire pixels of each row of images, where each data algorithm processes n pixels simultaneously when processing each row of images;

S101. Set a fluctuation status register, wherein the predetermined value of the fluctuation status register is X;

S102: Compare the R values of different pixels processed by the data algorithm, and at the same time compare the corresponding G and B values in each pixel;

S103. Set a discarding maximum value Y;

S104. Statistics start from the first clock cycle. If it is the same as the first clock cycle itself, the assignment of the data algorithm becomes the number of clock cycles multiplied by n. If a pixel R within the clock cycle is encountered , G, B have the same value, jump directly to step S109; if the value of the pixel R, G, B is different from the value of the pixel R, G, B in the previous clock cycle, then jump to Step S106, judging whether the number of the same clock cycles that have been counted is long enough;

S105. Set a discarded maximum condition value Hthro;

S106. If the counted number of clock cycles is not less than Hthro, record the values of R, G, and B of the same consecutive pixels and the number of the same pixels, put them into the matrix, and at the same time, put the R, G of the pixels , B value is set to the existing pixel R, G, B value consistency judgment value;

S107. If the number of pixels that are already the same when the last clock cycle is encountered is not less than the value Hthro, write down the R, G, and B values and the number of consecutive pixels that are the same;

Do not change the R, G, and B values to be determined until a self-consistent clock cycle is counted. At this time, change the R, G, and B values of the consistency determination value, and update the number of the same pixels;

S108. After one line of processing is completed, record the R, G, and B values of the remaining m groups of pixels and the number of pixels according to the value Hthro;

S109. Combine the R, G, and B values of the remaining m groups of pixels and the number of pixels into an m * 4 matrix; where it is separately determined whether the i-th group in the matrix is the same as each group after the i-th group , The same will add the number of the i-th group to the i-th group; and record the group with the largest number as the consistent R, G, B value of the row, and record the quantity value at the same time;

S110. Set a maximum discard time Hth for each line;

S111. Compare the quantity value in step S109 with Hth. If the quantity is greater than Hth, then the i-th line is the same, and then jump to step S108 for execution; if the quantity value is less than Hth, execute S112;

S112. Set a maximum discard value Vthro for each column, and perform calculation according to the same method as steps S106 to S111, so as to find out the same R, G, and B values of the entire frame of pixels and the number of rows of the pixels;

Wherein in step S101, each data algorithm will process 2, 4, or 8 pixels in the same clock cycle when processing each row of images; in step S102, if R, G in each group , The difference between B and B is not greater than X, the fluctuation state of this clock cycle is recorded as consistent; if the difference between R, G, and B in each group is greater than X, then this clock Periodic fluctuations are recorded as inconsistencies.

In the method for picture processing provided by the first embodiment of the present disclosure, in S106, the number of new pixels is updated to become the number of consecutively identical pixels times n.

In the method for picture processing provided by the first embodiment of the present disclosure, in the step S107, the number of identical pixels is updated to be n times the number of consecutive identical pixels.

In the method for picture processing provided by the first embodiment of the present disclosure, in the step S105, the discarded maximum condition value Hthro is set to 960.

In the method for picture processing provided by the first embodiment of the present disclosure, the data algorithm is twice the clock period when it is assigned.

In the method for image processing provided by the first embodiment of the present disclosure, the R, G, and B pixel values of the different pixels are one of 0-255.

In the method for picture processing provided in the first embodiment of the present disclosure, in step S109, when m = 4, the specific steps include,

Group 1 judges whether it is the same as groups 2, 3, and 4, respectively, and adds the number of groups to group 1;

Group 2 judges whether it is the same as group 3, and adds the number of the group to group 2;

Group 3 judges whether it is the same as group 4, and adds the number of groups to group 3 in the same way.

A second embodiment of a method for processing picture data according to the present disclosure includes the following steps:

S103. Set a discarding maximum value Y;

S105. Set a discarded maximum condition value Hthro;

S110. Set a maximum discard time Hth for each line;

S111. Compare the quantity value in step S109 with Hth. If the quantity is greater than Hth, then the i-th line is the same, and then jump to step S108 for execution; if the quantity value is less than Hth, perform step S112;

S112. Set a maximum discard value Vthro for each column, and perform calculation according to the same method as steps S106 to S111, so as to find out the same R, G, and B values of the entire frame of pixels and the number of rows of the pixels.

In the method for image processing provided by the second embodiment of the present disclosure, in the step S101, when processing each line of images, each data algorithm will process 2, 4, or 8 pixels in the same clock cycle point.

In the method for picture processing provided by the second embodiment of the present disclosure, in the step S102, if the difference between R, G, and B in each group is not greater than the X, then this clock cycle The fluctuation state of is recorded as self-consistency; if the difference of R, G and B in each group is greater than the X, then the fluctuation state of this clock cycle is recorded as self-inconsistency.

In the method for picture processing provided by the second embodiment of the present disclosure, in the step S106, at this time, the number of new pixels is updated to become the number of consecutive identical pixels times n.

In the method for picture processing provided by the second embodiment of the present disclosure, in the step S107, the update of the number of the same pixels becomes n times the number of the same pixels in succession.

In the method for picture processing provided in the second embodiment of the present disclosure, in step S105, the maximum condition value Hthro for discarding is set to 960.

In the method for picture processing provided by the second embodiment of the present disclosure, the data algorithm is twice the clock cycle when it is assigned.

In the method for image processing provided by the second embodiment of the present disclosure, the R, G, and B pixel values of the different pixels are one of 0-255.

In the method for picture processing provided by the second embodiment of the present disclosure, in step S109, when m = 4, the specific steps include,

Beneficial effect

Through the new program method, as can be seen from the above description, the present disclosure separately processes the image and compares the processed image with the set parameter value to obtain the required pixel value and the required number of pixels In this way, you can quickly find the maximum number of the same pixel points and their corresponding R, G, B pixel values from a frame, and also determine the number of rows where they are located. For these found pixel points, you can Special processing of these pictures is targeted to solve the problem that the existing technology cannot quickly find the same data maximum value and its RGB gray scale value from the same frame, and the accuracy is low.

BRIEF DESCRIPTION

In order to more clearly explain the embodiments or the technical solutions in the prior art, the following will briefly introduce the drawings required in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only for applications For some embodiments, those of ordinary skill in the art can obtain other drawings based on these drawings without creative work.

FIG. 1 is a schematic flowchart of the disclosed algorithm.

Embodiments of the invention

The technical solution in the disclosed embodiment will be described clearly and completely in conjunction with the drawings in the disclosed embodiment. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, but not all the embodiments.

A method for processing picture data is processed according to the steps provided by the present disclosure. The processing steps are as follows:

Specifically, in the data algorithm, 2, 4, or 8 pixels can be processed simultaneously in one clock cycle, that is, n = 2, n = 4, or n = 8.

S101. Set a dithering status register, wherein the predetermined value of the dithering status register is X;

S102. Compare the R, G, and B values of different pixels processed by the data algorithm. If the difference between R, G, and B in each group is not greater than the X, the fluctuation of this clock cycle The state is recorded as self-consistency; if the difference between R, G and B in each group is greater than the X, the fluctuation state of this clock cycle is recorded as self-inconsistency;

Specifically, taking the simultaneous processing of two pixels as an example, the processing in step S102 is: comparing R1-R2≤X, at the same time G1-G2≤X, and at the same time B1-B2≤X, when the above three comparison formulas are simultaneously established Then, the fluctuation state of this clock cycle is recorded as self-consistent; if the above three comparisons are not established at the same time, the fluctuation state of this clock cycle is recorded as self-inconsistent. Through such a method in order to quickly distinguish between different pixels.

S103. Set a discarding maximum value Y;

S104. Statistics start from the first clock cycle. If it is the same as the first clock cycle itself, the assignment of the data algorithm becomes the number of clock cycles multiplied by n. If a pixel R within the clock cycle is encountered , G, B have the same value, but the pixel R, G, B value is different from the pixel R, G, B value in the previous clock cycle, then according to step S106, the same Whether the number of clock cycles is long enough to judge;

S105. Set a discarded maximum condition value Hthro;

S106. If the counted number of clock cycles is not less than Hthro, record the values of R, G, and B of the same consecutive pixels and the number of the same pixels, and at the same time, the values of R, G, and B of the pixels Set to a new pixel consistency judgment value, at this time, the number of the new pixels is updated to be the number of the same consecutive pixels multiplied by n;

S107. If a different clock cycle is encountered, if the number of pixels that are already the same is not less than the value Hthro, write down the R, G, and B values and the number of consecutive pixels that are the same;

The R, G, and B values to be determined are not changed until a self-consistent clock cycle is counted. At this time, the R, G, and B values of the consistency determination value are changed, and the number of the same pixels is updated. Becomes n times the number of consecutive pixels that are the same;

S110. Set a maximum discard time Hth for each line;

S111. Compare the quantity value in step S109 with Hth. If the quantity is greater than Hth, the i-th row is consistent;

Preferably, in the step S100, if n = 2, it is equivalent to assigning n to 2 in a data (n) algorithm, so that the data (n) assignment becomes twice the clock period, so in The number of pixels obtained in subsequent steps needs to be multiplied by 2 to become the new number of pixels obtained.

After one line of processing, some recorded RGB values and their numbers will be left. The number of recorded groups depends on the selection of Hthro. The larger the Hthro, the stricter the conditions for writing down, and the fewer the number of groups recorded per line, then The less dynamic space required for each row, in the step S109, the maximum condition value Hthro is set to (3840/4) 960, then each row of statistics leaves 4 sets of RGB values and their numbers, so Form a 4 * 4 matrix as follows:

R1 G1 B1 Group 1

R2 G2 B2 Group 2

R3 G3 B3 Group 3

R4 G4 B4 Group 4

When processing the above matrix,

Group 1 determines whether the values in Groups 2, 3, and 4 are the same, and if they are the same, the number of groups is added to Group 1;

Group 2 determines whether the values in Groups 3 and 4 are the same, and if they are the same, the number of groups is added to Group 2;

Group 3 finally judges whether it is the same as group 4. If it is the same, the group number is added to group 3.

As shown in FIG. 1, a specific flowchart of a method for processing picture data according to the present disclosure is as follows:

S201: Extract the pixels of each row, and the statistical number of clock cycles clock is set to 0 at the beginning;

S202: According to the judgment condition, taking n = 2 as an example at this time, compare the R value, G value and B value of different pixels at the same time;

S203: Count the qualified values in S202 and record the corresponding quantity;

S204: Judge the number of clock cycles counted with Hthro;

S205: Write down the RGB value that satisfies the equation established in step S204, and write down the number;

S206: Combine the obtained RGB value of each row and its quantity into an operation matrix;

S207: Determine whether the i-th group in the matrix is the same as each group after the i-th group, and the same is to add the number of the i-th group to the i-th group;

S208: record the group with the largest number as the consistent R, G, and B values of the row, and record the quantity value No. final;

S209: Compare No. final obtained in S208 with the assigned Hth.

Finally, record the group with the largest number as the consistent R, G, and B values of the row, where the R, G, and B values are one of 0-255, and simultaneously record the number of the same pixels. After such processing, the number of the same RGB pixel values and their gray scale values can be accurately found.

In summary, the above provides a detailed description of a method for processing image data provided by the embodiments of the present disclosure. According to the embodiments of the present disclosure, the maximum number of identical pixels can be quickly found from a frame And the corresponding R, G, and B pixel values, as well as the number of rows where they are located. For these found pixel points, these pictures can be specifically processed to improve the accuracy of processing.

This article uses specific examples to explain the principles and implementation of the present disclosure. The descriptions of the above embodiments are only used to help understand the technical solutions and core ideas of the present disclosure; those of ordinary skill in the art should understand that they can still The technical solutions described in the foregoing embodiments are modified, or some of the technical features are equivalently replaced; and these modifications or replacements do not deviate from the scope of the technical solutions of the embodiments of the present disclosure.

Claims

A method for processing picture data, including the following steps:

S100. Acquire pixels of each row of images, where each data algorithm processes n pixels simultaneously when processing each row of images;

S101. Set a fluctuation status register, wherein the predetermined value of the fluctuation status register is X;

S102: Compare the R values of different pixels processed by the data algorithm, and at the same time compare the corresponding G and B values in each pixel;

S103. Set a discarding maximum value Y;

S104. Statistics start from the first clock cycle. If it is the same as the first clock cycle itself, the assignment of the data algorithm becomes the number of clock cycles multiplied by n. If a pixel R within the clock cycle is encountered , G, B have the same value, jump directly to step S109; if the value of the pixel R, G, B is different from the value of the pixel R, G, B in the previous clock cycle, then jump to Step S106, judging whether the number of the same clock cycles that have been counted is long enough;

S105. Set a discarded maximum condition value Hthro;

S106. If the counted number of clock cycles is not less than Hthro, record the values of R, G, and B of the same consecutive pixels and the number of the same pixels, put them into the matrix, and at the same time, put the R, G of the pixels , B value is set to the existing pixel R, G, B value consistency judgment value;

S107. If the number of pixels that are already the same when the last clock cycle is encountered is not less than the value Hthro, write down the R, G, and B values and the number of consecutive pixels that are the same;

Do not change the R, G, and B values to be determined until a self-consistent clock cycle is counted. At this time, change the R, G, and B values of the consistency determination value, and update the number of the same pixels;

S108. After one line of processing is completed, record the R, G, and B values of the remaining m groups of pixels and the number of pixels according to the value Hthro;

S109. Combine the R, G, and B values of the remaining m groups of pixels and the number of pixels into an m * 4 matrix; where it is separately determined whether the i-th group in the matrix is the same as each group after the i-th group , The same will add the number of the i-th group to the i-th group; and record the group with the largest number as the consistent R, G, B value of the row, and record the quantity value at the same time;

S110. Set a maximum discard time Hth for each line;

S111. Compare the quantity value in step S109 with Hth. If the quantity is greater than Hth, then the i-th line is the same, and then jump to step S108 for execution; if the quantity value is less than Hth, perform step S112;

S112. Set a maximum discard value Vthro for each column, and perform calculation according to the same method as steps S106 to S111, so as to find out the same R, G, and B values of the entire frame of pixels and the number of rows of the pixels;

Wherein in step S101, each data algorithm will process 2, 4, or 8 pixels in the same clock cycle when processing each row of images; wherein, in step S102, if R in each group , The difference between the three of G, B is not greater than the X, then the fluctuation state of this clock cycle is recorded as being consistent; if the difference of R, G, and B in each group is greater than the X, then The fluctuation state of this clock cycle is recorded as inconsistency.
The method for picture data processing according to claim 1, wherein in step S106, at this time, the number of new pixels is updated to become the number of consecutive identical pixels multiplied by n.
The method for picture data processing according to claim 1, wherein in the step S107, the number of identical pixels is updated to become n times the number of consecutive identical pixels.
The method for processing picture data according to claim 1, wherein in step S105, the discarded maximum condition value Hthro is set to 960.
The method for processing picture data according to claim 1, wherein the data algorithm is twice the clock period when assigned.
The method for processing picture data according to claim 1, wherein the R, G, and B pixel values of the different pixels are one of 0-255.
The method for processing picture data according to claim 1, wherein in step S109, when m = 4, the specific steps include,

Group 1 judges whether it is the same as groups 2, 3, and 4, respectively, and adds the number of groups to group 1;

Group 2 judges whether it is the same as group 3, and adds the number of the group to group 2;

Group 3 judges whether it is the same as group 4, and adds the number of groups to group 3 in the same way.
A method for processing picture data includes the following steps:

S100. Acquire pixels of each row of images, where each data algorithm processes n pixels simultaneously when processing each row of images;

S101. Set a fluctuation status register, wherein the predetermined value of the fluctuation status register is X;

S102: Compare the R values of different pixels processed by the data algorithm, and at the same time compare the corresponding G and B values in each pixel;

S103. Set a discarding maximum value Y;

S104. Statistics start from the first clock cycle. If it is the same as the first clock cycle itself, the assignment of the data algorithm becomes the number of clock cycles multiplied by n. If a pixel R within the clock cycle is encountered , G, B have the same value, jump directly to step S109; if the value of the pixel R, G, B is different from the value of the pixel R, G, B in the previous clock cycle, then jump to Step S106, judging whether the number of the same clock cycles that have been counted is long enough;

S105. Set a discarded maximum condition value Hthro;

S106. If the counted number of clock cycles is not less than Hthro, record the values of R, G, and B of the same consecutive pixels and the number of the same pixels, put them into the matrix, and at the same time, put the R, G of the pixels , B value is set to the existing pixel R, G, B value consistency judgment value;

S107. If the number of pixels that are already the same when the last clock cycle is encountered is not less than the value Hthro, write down the R, G, and B values and the number of consecutive pixels that are the same;

Do not change the R, G, and B values to be determined until a self-consistent clock cycle is counted. At this time, change the R, G, and B values of the consistency determination value, and update the number of the same pixels;

S108. After one line of processing is completed, record the R, G, and B values of the remaining m groups of pixels and the number of pixels according to the value Hthro;

S109. Combine the R, G, and B values of the remaining m groups of pixels and the number of pixels into an m * 4 matrix; where it is separately determined whether the i-th group in the matrix is the same as each group after the i-th group , The same will add the number of the i-th group to the i-th group; and record the group with the largest number as the consistent R, G, B value of the row, and record the quantity value at the same time;

S110. Set a maximum discard time Hth for each line;

S111. Compare the quantity value in step S109 with Hth. If the quantity is greater than Hth, the i-th line is the same, and then jump to step S108 for execution; if the quantity value is less than Hth, execute S112;

S112. Set a maximum discard value Vthro for each column, and perform calculation according to the same method in steps S106 to S111, so as to find out the same R, G, and B values of the entire frame of pixels and the number of rows of the pixels.
The method for processing picture data according to claim 8, wherein in step S101, when processing each line of images, each data algorithm processes 2, 4, or 8 pixels in the same clock cycle.
The method for processing picture data according to claim 8, wherein in step S102, if the difference between R, G, and B in each group is not greater than the X, then the fluctuation of the clock period The state is recorded as self-consistency; if the difference between R, G, and B in each group is greater than the X, the fluctuation state of this clock cycle is recorded as self-inconsistency.
The method for picture data processing according to claim 8, wherein in step S106, at this time, the number of new pixels is updated to become the number of consecutive identical pixels times n.
The method for picture data processing according to claim 8, wherein in step S107, the number of identical pixels is updated to be n times the number of consecutive identical pixels.
The method for processing picture data according to claim 8, wherein in step S105, the discarded maximum condition value Hthro is set to 960.
The method for processing picture data according to claim 8, wherein the data algorithm is twice the clock period when assigned.
The method for processing picture data according to claim 8, wherein the R, G, and B pixel values of the different pixels are one of 0-255.
The method for processing picture data according to claim 8, wherein in step S109, when m = 4, the specific steps include,

Group 1 judges whether it is the same as groups 2, 3, and 4, respectively, and adds the number of groups to group 1;

Group 2 judges whether it is the same as group 3, and adds the number of the group to group 2;

Group 3 judges whether it is the same as group 4, and adds the number of groups to group 3 in the same way.