Cross-Component Candidate Lists for Chroma Video Coding
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Solution Overview
Problem
Existing video coding technologies, such as HEVC and VVC, face challenges in improving coding efficiency and performance, particularly in handling chroma blocks, due to limitations in cross-component prediction methods.
Innovation Solution
Implementing a cross-component prediction candidate list for chroma blocks, which involves generating and applying a prediction model to improve coding efficiency and performance by leveraging cross-component prediction techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional video coding technologies (HEVC, VVC) are used for chroma block encoding, then the coding process is simpler, but coding efficiency and performance are insufficient
Solution Approach 1:
The patent segments the prediction process by separating luma and chroma prediction operations. It applies cross-component prediction specifically to chroma blocks by deriving prediction candidates from luma neighbors, rather than treating all blocks uniformly. This segmentation allows optimized prediction for chroma without unnecessarily complicating the overall coding process.
Solution Approach 2:
The patent changes the prediction parameters for chroma blocks by introducing cross-component prediction modes that utilize luma neighbor information. Instead of using only intra-chroma prediction, the system derives chroma prediction candidates from luma blocks through linear models or gradient calculations, fundamentally changing how chroma prediction parameters are obtained.
2Manufacturing precision
If cross-component prediction is applied to chroma blocks, then coding performance improves, but the complexity of generating and applying prediction candidate lists increases
Solution Approach 1:
The patent performs preliminary action by deriving cross-component prediction candidates from luma neighbors before the actual chroma prediction step. The system pre-calculates prediction candidates using linear models or gradient-based methods from already-decoded luma blocks, making the chroma prediction process more accurate without adding significant complexity during the main encoding/decoding phase.
Solution Approach 2:
The patent introduces an intermediary mechanism where luma blocks serve as mediators for chroma prediction. Instead of directly predicting chroma from scratch, the system uses luma neighbor information as an intermediary source to derive chroma prediction candidates, improving accuracy by leveraging the correlation between luma and chroma components.
3Productivity
If traditional intra prediction is used for chroma, then the processing is faster, but the coding performance and compression ratio are limited
Solution Approach 1:
The patent merges luma and chroma prediction processes by applying cross-component prediction where chroma prediction candidates are derived from luma neighbors. This combining of luma and chroma processing allows the system to achieve better compression ratios by exploiting the correlation between luminance and chrominance components, while still maintaining reasonable processing speeds through efficient candidate derivation.
Data Source
AI summary
Embodiments of the disclosure provide a solution for video processing. A method for video processing is proposed. The method includes: generating, for a conversion between a video unit of a video and a bitstream of the video, a cross-component prediction candidate list for a chroma block associated with the video unit; determining a prediction of the current block by applying the cross-component prediction candidate list to the video unit; and performing the conversion based on the prediction.