Cross-Component Sample Adaptive Offset for Chroma Coding Efficiency
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Solution Overview
Problem
Existing video coding technologies face challenges in efficiently compressing luma and chroma components due to the lack of effective methods that exploit the cross-component relationships between them, leading to suboptimal coding efficiency.
Innovation Solution
Implementing a method and apparatus that utilize cross-component sample adaptive offset (CCSAO) techniques to improve coding efficiency by selecting offsets based on classifiers derived from residual sample values of the luma component to modify sample values of the chroma component during encoding and decoding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional video coding methods are used without exploiting cross-component relationships, then the coding process is simpler, but coding efficiency is suboptimal
Solution Approach 1:
The patent merges the coding processes of luma and chroma components by exploiting their cross-component relationships. Specifically, it combines residual sample values from the luma component with chroma component data to generate improved chroma predictions, thereby improving coding efficiency through integrated processing rather than separate independent coding
Solution Approach 2:
The patent applies multi-functionality by using the luma residual sample values for multiple purposes: not only for luma reconstruction but also for generating chroma offsets and improving chroma prediction. This universal use of luma information across different color components improves overall coding efficiency without requiring additional separate processing streams
2Productivity
If cross-component sample adaptive offset techniques are implemented to exploit relationships between luma and chroma, then coding efficiency is improved, but computational complexity increases
Solution Approach 1:
The patent changes parameters by dynamically selecting offset values based on the characteristics of residual sample values from the luma component. Instead of using fixed or independently determined chroma offsets, the system adjusts chroma offset parameters according to the statistical properties and magnitude of luma residuals, thereby improving efficiency through adaptive parameter selection
Solution Approach 2:
The patent uses copying by deriving chroma offset information from luma residual data. The statistical characteristics and patterns observed in luma residuals are copied and applied to generate chroma component offsets, leveraging the correlation between color components to improve chroma prediction without requiring separate complex modeling for each component
3Productivity
If offsets are selected based on classifiers derived from residual sample values, then compression optimization is improved, but processing time increases
Solution Approach 1:
The patent applies preliminary action by pre-calculating and classifying residual sample value characteristics during the encoding process. Classification results and offset selections are determined in advance based on residual patterns, allowing the decoder to simply apply pre-determined offsets without performing complex real-time analysis, thereby reducing processing time at the decoding stage
Data Source
AI summary
Methods and devices are provided for video coding. In one method, a decoder may receive a video signal that comprises a first component and the second component and receive a plurality of offsets associated with the second component. Furthermore, the decoder may obtain a classifier associated with the second component according to a residual sample value of the first component and selecting an offset from the plurality of offsets for the second component according to the classifier. Moreover, the decoder may obtain a modified sample value of the second component based on the offset that is selected.