Residual Coding Using Sub-Block Rice Initialization
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Solution Overview
Problem
High-resolution, high-quality image/video data requires efficient compression techniques to reduce transmission and storage costs, especially with the growing demand for virtual reality, augmented reality, and immersive media, as existing methods struggle to effectively compress and transmit such data.
Innovation Solution
A method and device for enhancing image/video coding efficiency by performing a binarization process on residual information based on a rice parameter, with a maximum value of 3, to derive and initialize rice parameters for sub-blocks within current blocks, optimizing the encoding and decoding processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If conventional compression techniques are used for high-resolution image/video data, then transmission and storage costs increase, but image quality and resolution requirements cannot be met
Solution Approach 1:
The current block is divided into multiple sub-blocks for independent residual coding. Each sub-block has its own rice parameter initialization, allowing differentiated compression strategies for different regions, thus maintaining image quality while reducing overall data volume
Solution Approach 2:
Different rice parameters are initialized for different sub-blocks based on local characteristics. The binarization process uses these localized parameters to optimize compression for each region, preserving important local image details while achieving overall data reduction
2Productivity
If residual coding efficiency is improved through binarization process, then compression ratio increases, but computational complexity increases
Solution Approach 1:
The rice parameter values are changed and optimized specifically for residual coding applications. By initializing rice parameters within a maximum value of 3 and adapting them to sub-block characteristics, the binarization process achieves better compression efficiency while controlling computational complexity through parameter optimization
Data Source
AI summary
A method for decoding a picture performed by a decoding apparatus according to the present disclosure includes receiving a bitstream including residual information, deriving a quantized transform coefficient for a current block based on the residual information included in the bitstream, deriving a transform coefficient from the quantized transform coefficient based on a dequantization process, deriving a residual sample for the current block by applying an inverse transform to the derived transform coefficient, and generating a reconstructed picture based on the residual sample for the current block.