WO2020113766A1 - Procédé de compression de table de compensation - Google Patents

Procédé de compression de table de compensation Download PDF

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Publication number
WO2020113766A1
WO2020113766A1 PCT/CN2019/071033 CN2019071033W WO2020113766A1 WO 2020113766 A1 WO2020113766 A1 WO 2020113766A1 CN 2019071033 W CN2019071033 W CN 2019071033W WO 2020113766 A1 WO2020113766 A1 WO 2020113766A1
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Prior art keywords
compensation table
sub
block
quantization
compression method
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PCT/CN2019/071033
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English (en)
Chinese (zh)
Inventor
程琳
邓宇帆
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深圳市华星光电半导体显示技术有限公司
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Publication of WO2020113766A1 publication Critical patent/WO2020113766A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/14—Digital output to display device ; Cooperation and interconnection of the display device with other functional units
    • G06F3/1407—General aspects irrespective of display type, e.g. determination of decimal point position, display with fixed or driving decimal point, suppression of non-significant zeros
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T9/00—Image coding
    • G06T9/007—Transform coding, e.g. discrete cosine transform

Definitions

  • the invention relates to the field of image processing, in particular to a compensation table compression method.
  • Data compression is a relatively mature technology for reducing data size. It is applied to the data stored in the memory subsystem of the computer system to increase the storage capacity. Data compression is also used when data is transferred between different subsystems within a computer system, or generally when the transfer is performed between two points in a data communication system that includes a communication network.
  • Data compression requires two basic operations: 1. Compression (also called encoding). Compression is to take uncompressed data as input and pass the corresponding codeword (also called encoding, word code or code in the literature) Replace data values to convert uncompressed data into compressed data: 2. Decompression (also called decoding). Decompression uses compressed data as input and replaces the codeword with the corresponding data value. The compressed data is converted to uncompressed. Data compression can be lossless or lossy, depending on whether the actual data value after decompression is exactly the same as the original data value before compression (lossless), or whether the data value after decompression is different The original data value and the original value cannot be obtained (lossy type). Compression and decompression can be implemented in software, or hardware, or a combination of software and hardware to implement corresponding methods, devices, and systems.
  • the compensation table is usually used to store the compensation information of each pixel.
  • the driver board looks up the compensation table, adjusts the signal, and adjusts the signal in the dark area of the panel up, and the signal in the bright area down, showing a uniform display effect.
  • each pixel corresponds to a set of compensation information, and each set of compensation information contains one or more compensation data.
  • the physical meaning of the compensation data depends on the algorithm, which is usually the adjustment value of a specific gray scale, and some algorithms set it to the voltage value to be adjusted.
  • the lossy compression algorithm of the compensation table in the prior art will visually see the loss.
  • the size of the compensation table It is equal to the number of panel pixels multiplied by the size of each set of compensation information. If a 55-inch UHD (Ultra High Definition) RGB panel is compensated (each pixel includes three sub-pixels of red, green and blue), assuming that each sub-pixel compensation information is 24 bits, the compensation table data The quantity is 2160*3840*24bit*3 ⁇ 597Mb.
  • the compensation table of the prior art occupies a lot of system storage resources, which has high requirements on the hardware system, and the process of transmitting and burning data on the production line takes time.
  • the purpose of the present invention is to provide a compensation table compression method, which can obtain the optimal quantization step without iteration, reduce the occupation of memory space, save the hardware resources of the system, and can reduce the cost and reduce the cost of transmitting and burning data time.
  • the present invention provides a compensation table compression method, including the following steps:
  • Step S1 Divide the original compensation table into multiple sub-blocks of the same size in the air domain
  • Step S2 Multiply the original compensation table divided into multiple sub-blocks by the sobel operator to obtain a gradient vector, and calculate the variance of each block separately;
  • Step S4 Each sub-block is quantized separately according to its corresponding quantization step size to obtain a quantization compensation table, and the coding algorithm is used to compress the quantization compensation table.
  • Step S5 Decompress the compressed quantization compensation table, and then dequantize each sub-block according to the information in the quantization compensation table to reconstruct the original compensation table.
  • each sub-block is 8*8.
  • step S2 the edge of each sub-block is detected by the sobel operator.
  • step S3 the calculation formula of the quantization step size is obtained through a visual lossless subjective experiment, where a and b are parameters obtained by fitting the results of the visual lossless subjective experiment.
  • the invention also provides a compensation table compression method, including the following steps:
  • Step S1' DCT transform the original compensation table, convert the original compensation table from the spatial domain to the frequency domain, and divide it into multiple sub-blocks of the same size;
  • Step S4' Each sub-block is quantized separately according to its corresponding quantization step size to obtain a quantization compensation table, and the encoding algorithm is used to compress the quantization compensation table.
  • Step S5' Decompress the compressed quantization compensation table, and then inverse quantize and inverse DCT transform each sub-block to reconstruct the original compensation table according to the information in the quantization compensation table.
  • each sub-block is 8*8.
  • the size of the lower right corner area of the DCT coefficient of each sub-block is 4*4; the DC coefficient is the value of the upper left corner of each sub-block.
  • step S3' the calculation formula of the quantization step size is obtained through a visual lossless subjective experiment, where a and b are parameters obtained by fitting the results of the visual lossless subjective experiment.
  • the invention also provides a compensation table compression method, including the following steps:
  • Step S1' DCT transform the original compensation table, convert the original compensation table from the spatial domain to the frequency domain, and divide it into multiple sub-blocks of the same size;
  • Step S4' each sub-block is quantized separately according to its corresponding quantization step size to obtain a quantization compensation table, and the coding algorithm is used to compress the quantization compensation table;
  • Step S5' by decompressing the compressed quantization compensation table, and then dequantizing and inverse DCT transforming each sub-block to reconstruct the original compensation table according to the information in the quantization compensation table;
  • each sub-block is 8*8.
  • the compensation table compression method of the present invention makes the human eye not notice the quality loss of the original compensation table through visual lossless compression of the compensation table, and greatly increases the compression efficiency, compared with the existing compensation table compression algorithm
  • the invention can obtain the optimal quantization step without iteration, reduce the occupation of memory space, save the hardware resources of the system, and can reduce the cost and the time spent in transferring and burning data.
  • FIG. 1 is a flowchart of a first embodiment of a compensation table compression method of the present invention
  • FIG. 2 is a logic diagram of a first embodiment of a compensation table compression method of the present invention
  • FIG. 3 is a flowchart of a second embodiment of the compensation table compression method of the present invention.
  • FIG. 4 is a logic diagram of a second embodiment of the compensation table compression method of the present invention.
  • the present invention provides a first embodiment of a compensation table compression method, including the following steps:
  • Step S1 Divide the original compensation table into multiple sub-blocks of the same size in the air domain
  • Step S2 Multiply the original compensation table divided into multiple sub-blocks by the sobel operator to obtain a gradient vector, and calculate the variance of each block separately;
  • Step S4 Each sub-block is quantized separately according to its corresponding quantization step size to obtain a quantization compensation table, and the coding algorithm is used to compress the quantization compensation table.
  • step S5 Decompressing the compressed quantization compensation table, and then dequantizing each sub-block according to the information in the quantization compensation table, the original compensation table can be reconstructed.
  • each sub-block is 8*8, that is, each sub-block corresponds to 8 rows and 8 columns of pixels (a total of 64 pixels) of compensation information.
  • step S2 the edge of each sub-block is detected by the sobel operator to determine the location of each sub-block.
  • step S3 the calculation formula of the quantization step size can be obtained according to the visual lossless subjective experiment, so as to losslessly compress the quantization compensation table, where a and b are parameters obtained by fitting the results of the visual lossless subjective experiment.
  • the present invention uses visual lossless compression compensation table to make human eyes not notice the quality loss of the original compensation table, and greatly increases the compression efficiency.
  • the present invention does not require iteration It can obtain the best quantization step size, reduce the occupation of memory space, save the hardware resources of the system, and can reduce the cost and reduce the time spent in transferring and burning data.
  • the present invention provides a second embodiment of a compensation table compression method, including the following steps:
  • Step S1' Perform a DCT transform (discrete cosine transform) on the original compensation table, convert the original compensation table from the spatial domain to the frequency domain, and divide it into multiple sub-blocks of the same size;
  • DCT transform discrete cosine transform
  • Step S4' Each sub-block is quantized separately according to its corresponding quantization step size to obtain a quantization compensation table, and the encoding algorithm is used to compress the quantization compensation table.
  • step S5' decompressing the compressed quantization compensation table, dequantizing each sub-block according to the information in the quantization compensation table, and inversely DCT transforming each sub-block to reconstruct the original compensation table.
  • each sub-block is 8*8, that is, each sub-block corresponds to 8 rows and 8 columns of pixels (a total of 64 pixels) of compensation information.
  • the size of the lower right corner area of each sub-block DCT coefficient is 4*4, that is, the compensation information of the lower right corner area of each sub-block DCT coefficient corresponds to 4 rows and 4 columns of pixels (a total of 16 pixels); the DC coefficient is in each sub-block The value in the upper left corner.
  • the calculation formula of the quantization step size can be obtained according to the visual lossless subjective experiment, and thus the lossless compression quantization compensation table, where a and b are parameters obtained by fitting the results of the visual lossless subjective experiment.
  • the present invention uses visual lossless compression compensation table to make human eyes not notice the quality loss of the original compensation table, and greatly increases the compression efficiency.
  • the present invention does not require iteration It can obtain the best quantization step size, reduce the occupation of memory space, save the hardware resources of the system, and can reduce the cost and reduce the time spent in transferring and burning data.
  • the compensation table compression method of the present invention compresses the compensation table visually, so that human eyes cannot perceive the quality loss of the original compensation table, and greatly increases the compression efficiency.
  • the invention can obtain the optimal quantization step size without iteration, reduce the occupation of the memory space, save the hardware resources of the system, and can reduce the cost and the time spent in transferring and burning data.

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  • General Physics & Mathematics (AREA)
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  • Discrete Mathematics (AREA)
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Abstract

La présente invention concerne un procédé de compression de table de compensation. Dans le procédé de compression de table de compensation, au moyen d'une table de compensation de compression sans perte visuelle, la perte de qualité d'une table de compensation d'origine n'est pas détectée par un oeil humain, et l'efficacité de compression est fortement augmentée. Par comparaison avec un algorithme de compression de table de compensation existant, la présente invention peut obtenir une taille de pas de quantification optimale sans itération, réduit l'occupation de l'espace mémoire, économise les ressources matérielles d'un système, peut réduire les coûts, et réduit le temps consommé pour la transmission et le rodage des données.
PCT/CN2019/071033 2018-12-04 2019-01-09 Procédé de compression de table de compensation WO2020113766A1 (fr)

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