Cross-Component Sample Adaptive Offset for Artifact Reduction
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Solution Overview
Problem
Existing video coding standards like HEVC and VVC do not effectively utilize the correlation between color components to refine reconstructed samples, leading to compression artifacts such as banding and ringing.
Innovation Solution
Implement Cross-Component Sample Adaptive Offset (CCSAO) that classifies reconstructed samples using the correlation between luma and chroma components to apply adaptive offsets, enhancing the refinement of reconstructed samples.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If traditional video coding standards (HEVC/VVC) are used without cross-component correlation, then the coding process is simpler, but compression artifacts such as banding and ringing occur and picture quality deteriorates
Solution Approach 1:
The patent combines luma and chroma components to form a composite classification approach. By using joint luma-chroma sample pairs for category classification, the method leverages the correlation between color components to reduce compression artifacts, effectively creating a composite filtering mechanism that improves picture quality while managing complexity through shared offset tables.
2Productivity
If cross-component sample adaptive offset is applied, then picture quality and compression efficiency improve, but the computational complexity increases
Solution Approach 1:
The patent merges the classification processes for luma and chroma components by using joint luma-chroma sample pairs. This combining approach allows the method to exploit inter-component correlations to improve compression efficiency. The offset tables are also designed to be shared or jointly constructed, reducing the overall computational burden compared to completely separate processing.
Solution Approach 2:
The offset tables constructed in this method serve multiple purposes: they are used for both luma and chroma component refinement, and they leverage correlations across different color components. This multi-functional use of the same offset structures improves compression efficiency without requiring separate complex processing for each component.
3Object-affected harmful factors
If cross-component sample adaptive offset is applied, then picture quality improves, but the processing complexity increases
Solution Approach 1:
The patent combines luma and chroma components to form a composite classification approach. By using joint luma-chroma sample pairs for category classification, the method leverages the correlation between color components to reduce compression artifacts, effectively creating a composite filtering mechanism that improves picture quality while managing complexity through shared offset tables.
Data Source
AI summary
A video coding method for cross-component sample adaptive offset (CCSAO) is provided. A video coder receives a current sample at a current pixel position of a current block being coded. The video coder selects one luma sample and two chroma samples as luma and chroma collocated samples of the pixel position. Only one or a subset of multiple candidate luma samples in a vicinity of the current pixel position is eligible to be the luma collocated sample of the current pixel position. The video coder selects a pixel category from multiple pixel categories based on the values of the selected luma and chroma collocated samples for the current pixel position. The video coder performs a lookup for an offset based on the selected pixel category. The video coder updates the current sample by applying the offset. The video coder encodes/decodes the current block based on the updated current sample.