Cross-Component Sample Adaptive Offset Classification
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Solution Overview
Problem
Current Cross-Component Sample Adaptive Offset (CCSAO) designs in video coding, such as in the Versatile Video Coding (VVC) standard, face inefficiencies due to the lack of consideration for chroma information in classification, uneven sample distribution in bands, and limited co-located luma sample positions, leading to inaccurate offsets and reduced coding efficiency.
Innovation Solution
The proposed method introduces chroma information into the CCSAO classification process, uses a non-uniform band offset classification method to balance sample distribution, and allows for different positions of co-located luma samples based on video formats, thereby improving the accuracy of offset determination and enhancing coding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If chroma information is not considered in CCSAO classification, then the classification process is simpler, but the offset accuracy is reduced
Solution Approach 1:
The patent merges luma and chroma classification processes into a unified CCSAO classification mechanism. The chroma sample classification uses both luma sample information and chroma sample information together, combining multiple data sources to achieve more accurate offset determination while maintaining a coherent processing framework.
Solution Approach 2:
The patent introduces chroma dimension to the existing luma-based classification system. By adding chroma sample information as an additional dimension of classification, the system moves from one-dimensional (luma only) to two-dimensional (luma and chroma) classification, enhancing offset accuracy without fundamentally redesigning the entire process.
2Measurement precision
If uniform band offset classification is used, then the implementation is simpler, but sample distribution becomes uneven leading to inaccurate offsets
Solution Approach 1:
The patent applies local quality by creating non-uniform band offsets that adapt to local sample distribution characteristics. Different band offsets are assigned based on the actual distribution of chroma samples within each luma band, allowing each region to have optimized offset values that match its specific sample density and characteristics.
Solution Approach 2:
The patent changes the offset parameter from uniform fixed values to non-uniform adaptive values. The band offset is calculated based on the distribution of chroma samples in each luma band, dynamically adjusting the offset parameter to match the local sample characteristics and achieve more accurate compensation.
3Adaptability or versatility
If only fixed positions of co-located luma samples are used, then the processing is faster, but the adaptability to different video formats is reduced
Solution Approach 1:
The patent introduces dynamic selection of co-located luma sample positions based on the specific video format and chroma sampling configuration. Instead of using fixed positions, the system dynamically determines which luma samples are co-located with chroma samples according to the actual video parameters, enabling adaptation to various formats while maintaining efficient processing through structured selection criteria.
Data Source
AI summary
A method for video data processing includes: determining a category index of a target chroma sample, wherein the category index is determined based on a first reconstructed value associated with a co-located luma sample and a second reconstructed value associated with the target chroma sample; determining an offset based on the category index; and adding the offset to a third reconstructed value associated with the target chroma sample.