Transform Coefficient Sign Prediction Contexts for Video Coding
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Solution Overview
Problem
Existing video coding techniques do not effectively utilize the position of transform coefficients and coding modes to determine contexts for sign prediction syntax elements, leading to suboptimal coding efficiency.
Innovation Solution
Determine contexts for coding sign prediction syntax elements based on the position of transform coefficients and coding modes used, rather than solely on transform coefficient magnitudes, to improve coding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If contexts for sign prediction syntax elements are determined solely based on transform coefficient magnitudes, then the coding process is simpler, but coding efficiency is suboptimal
Solution Approach 1:
The patent applies local quality by creating different context determination methods for different regions of the transform coefficient block. Specifically, it distinguishes between luma and chroma components, and within luma, separates DC and non-DC coefficients. Each region uses an appropriate context model based on its characteristics, thereby improving overall coding efficiency without uniformly increasing complexity across the entire block.
Solution Approach 2:
The patent segments the transform coefficient block into different regions (luma DC, luma non-DC, chroma) and applies different context determination strategies to each segment. This segmentation allows the system to optimize for each specific region's characteristics while maintaining manageable complexity for each individual segment, resolving the contradiction between overall efficiency and complexity.
2Productivity
If transform coefficients are not partitioned into different regions, then the coding process is simpler, but coding efficiency is reduced due to inability to capture regional characteristics
Solution Approach 1:
The patent implements local quality by recognizing that different regions of the transform coefficient block have different statistical characteristics. Luma DC coefficients, luma non-DC coefficients, and chroma coefficients each exhibit different sign prediction patterns. By applying region-specific context models, the patent captures these local characteristics to improve coding efficiency.
Solution Approach 2:
The patent segments the transform coefficient block into distinct regions (luma DC, luma non-DC, chroma) and applies different context determination methods to each segment. This segmentation strategy captures regional characteristics effectively while keeping the complexity of each individual segment manageable, thus resolving the contradiction between capturing regional characteristics and maintaining simplicity.
Data Source
AI summary
A video coder may code a sign prediction syntax element that indicates whether a sign prediction hypothesis is correct for a transform coefficient. The video coder may code the sign prediction syntax element using a context-based coding process. The video coder may determine a context for coding the sign prediction syntax element based on a position of the transform coefficient in the block of video data. The context may be further based on a coding mode used to code the block.