Chroma Prediction Fusion for Higher-Quality Video Coding
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Solution Overview
Problem
Existing video coding technologies, such as MPEG-2, MPEG-4, ITU-T.263, ITU-T.264/MPEG-4 AVC, and ITU-T.265 HEVC, require improvements in chroma component prediction to enhance coding quality.
Innovation Solution
A method for video processing that determines a set of candidate cross-component prediction (CCP) models for a chroma component based on coding information and uses a candidate prediction fusion scheme to improve chroma prediction, implemented in a video encoder and decoder.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional video coding technologies (MPEG-2, MPEG-4, HEVC) are used, then coding quality can be maintained at acceptable levels, but chroma component prediction quality is insufficient and needs improvement
Solution Approach 1:
The patent divides the chroma prediction process into multiple candidate models (first CCP model, second CCP model, third CCP model) with different prediction directions and methods. Each model is evaluated and selected or combined based on specific criteria, allowing the system to achieve high prediction quality by choosing from segmented prediction options rather than using a single complex model
Solution Approach 2:
The patent combines multiple chroma prediction models and fusion schemes into a unified selection process. The system merges candidate models with different prediction strategies (angular prediction, planar prediction, cross-component prediction) and combines them through fusion schemes to produce the final chroma prediction, achieving superior quality through integration of multiple approaches
2Manufacturing precision
If multiple candidate CCP models and fusion schemes are evaluated, then chroma prediction quality improves, but processing time and computational complexity increase
Solution Approach 1:
The patent performs preliminary evaluation of multiple candidate CCP models and fusion schemes before final chroma prediction is generated. By pre-evaluating and ranking the candidate models based on prediction accuracy and computational cost, the system can quickly select the optimal model without needing to exhaustively evaluate all possibilities during real-time processing
Solution Approach 2:
The patent evaluates more candidate models and fusion schemes than strictly necessary (excessive action), but uses this over-evaluation to identify the optimal prediction quality-time tradeoff point. By considering a broader set of candidates than the minimum required, the system ensures optimal performance while controlling processing time through selective application of the best models
Data Source
AI summary
Embodiments of the present disclosure provide a solution for video processing. A method for video processing is proposed. The method comprises: determining, for a conversion between a current video block of a video and a bitstream of the video, a set of candidate cross-component prediction (CCP) models for a chroma component of the current video block based on coding information associated with the current video block; determining a prediction for the chroma component based on the set of candidate CCP models and a candidate prediction fusion scheme; and performing the conversion based on the prediction.