Cross-Component Adaptive Offset Quantization for Lower Video Bit Rates
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Solution Overview
Problem
Existing video coding technologies face challenges in efficiently compressing both luma and chroma components, leading to suboptimal coding efficiency and increased bit rates.
Innovation Solution
Implementing a cross-component sample adaptive offset (CCSAO) quantization method that utilizes predefined or signaled offset quantization control syntax and step sizes to enhance the coding efficiency of luma and chroma components by leveraging their cross-component relationships.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional separate quantization methods are used for luma and chroma components, then the encoding process is simple, but the coding efficiency is suboptimal and bit rates are increased
Solution Approach 1:
The patent combines the quantization processes of luma and chroma components into a unified CCSAO framework. The encoder applies cross-component sample adaptive offset to both luma and chroma blocks using shared quantization parameters and offset tables, merging previously separate processing streams into an integrated system that improves coding efficiency while managing complexity through parameter sharing.
2Measurement precision
If higher quantization precision is used for both luma and chroma, then video quality is maintained, but bit rate increases
Solution Approach 1:
The patent employs parameter changes by introducing quantization step sizes and offset values that are selectively applied to luma and chroma components. The encoder uses quantization parameters (e.g., QP_Y, QP_Cb, QP_Cr) to control the precision of offset application, allowing adaptive adjustment of video quality and bit rate trade-offs through parameter modification rather than fixed high-precision processing.
Solution Approach 2:
The patent applies local quality by using sample adaptive offset techniques that classify samples into different groups (e.g., edge regions, smooth regions) and apply different quantization offsets to different regions. This allows higher precision to be applied only where necessary (e.g., edge regions requiring better preservation) while using coarser quantization in smooth regions, maintaining video quality while reducing overall bit rate.
Data Source
AI summary
Method and devices are provided for video coding. In the method, a decoder obtains a cross-component sample adaptive offset (CCSAO) quantization associated with an offset quantization control syntax and a quantization step size that are predefined or indicated by an encoder at at least one level. Furthermore, the decoder obtains a CCSAO based on the CCSAO quantization and adds the CCSAO to a reconstructed sample for prediction.