Residual Coefficient Rearrangement for Video Coding Efficiency
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Solution Overview
Problem
High-resolution and high-quality image data requires efficient compression techniques to reduce transmission and storage costs, as conventional methods struggle with the increased amount of information needed for HD and UHD images.
Innovation Solution
The method involves deriving and rearranging residual coefficients in an image coding system, specifically through entropy decoding, rearrangement, and entropy encoding, to improve coding efficiency by addressing the lack of correlation between residual coefficients in the pixel domain.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional image coding methods are used for high-resolution images, then image quality is maintained, but transmission cost and storage cost increase due to increased data amount
Solution Approach 1:
The patent applies parameter changes by transforming residual coefficients from spatial domain to frequency domain using transform processes (DCT, DST, or other transforms). This changes the representation parameters of the image data, concentrating energy in fewer coefficients and enabling more efficient compression while maintaining image quality
Solution Approach 2:
The patent segments the image into multiple blocks and processes residual coefficients separately for each block. By dividing the image data into smaller units and applying transform and quantization independently to each block, the system achieves better compression efficiency while maintaining overall image quality
2Productivity
If residual coefficients are coded directly without rearrangement, then coding process is simple, but coding efficiency is reduced due to lack of correlation between coefficients
Solution Approach 1:
The patent performs preliminary action by rearranging residual coefficients into a specific order (such as diagonal scanning or zigzag pattern) before entropy encoding. This preliminary reorganization exploits the correlation structure of transform coefficients, placing non-zero coefficients in predictable positions that can be encoded more efficiently
Solution Approach 2:
The patent replaces direct spatial-domain coding with a frequency-domain-based coding mechanism. By substituting the mechanical approach of coding coefficients in their original spatial positions with a transform-based approach followed by systematic rearrangement, the system achieves better exploitation of coefficient correlations and improved coding efficiency
Data Source
AI summary
A video decoding method performed by a decoding device according to the present document comprises the steps of: entropy decoding residual information for a current block to derive residual coefficients for the current block; rearranging the residual coefficients; deriving residual samples of the current block on the basis of the rearranged residual coefficients; and restoring a current picture on the basis of the residual samples.