Residual Signal Coding via Adaptive Sub-Block Transform Units
Find Innovative SolutionsGenerate Solutions
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 high-definition and ultra-high-definition images.
Innovation Solution
A method and device for coding residual signals by adaptively changing sub-block sizes of transform units and efficiently scanning/decoding transform coefficients, using new syntax elements to improve coding efficiency and reduce data requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional compression techniques are used for high-resolution images, then transmission and storage costs increase, but image quality and resolution requirements cannot be met
Solution Approach 1:
The transform unit is divided into multiple sub-blocks, and transform coefficients are scanned and coded by unit of sub-blocks. This segmentation allows for more granular processing of residual signals, enabling efficient compression while maintaining image quality by adapting to local frequency characteristics in different sub-block regions.
Solution Approach 2:
Different sub-blocks within a transform unit can have different scanning and coding strategies applied based on their local characteristics. This allows the encoding process to adapt to local frequency distributions and energy concentrations, optimizing compression efficiency for each region while preserving overall image quality.
2Productivity
If transform coefficients are coded by unit of sub-blocks, then coding efficiency increases, but processing complexity increases
Solution Approach 1:
By dividing the transform unit into sub-blocks and processing transform coefficients in smaller units, the patent achieves better coding efficiency through more adaptive entropy coding. The segmentation enables context-adaptive binary arithmetic coding (CABAC) to work more effectively on smaller coefficient groups, improving compression ratios while the modular structure helps manage processing complexity.
Solution Approach 2:
The patent introduces dynamic sub-block partitioning and adaptive scanning strategies that can be adjusted based on the characteristics of the residual signal. This dynamic approach allows the system to optimize between coding efficiency and processing complexity by adapting the level of subdivision and processing intensity to the actual content being encoded.
Data Source
AI summary
An image decoding method according to the present invention comprises the steps of: deriving quantized transform coefficients by unit of sub-blocks in a transform unit on the basis of residual information included in a bitstream; deriving transform coefficients on the basis of the quantized transform coefficients; generating a residual sample on the basis of the transform coefficients; generating a prediction sample on the basis of an inter prediction or an intra prediction; and restoring an image on the basis of the residual sample and the prediction sample. According to the present invention, a quantity of data required for a residual signal can be reduced, and an overall coding efficiency can be improved.