History-Based CCP Models for Efficient Video Block 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, ITU-T.265 HEVC, and VVC, face challenges in improving coding efficiency and effectiveness.
Innovation Solution
Implementing a method for video processing that involves determining cross-component prediction (CCP) models based on history tables (HT) and updating these models before or after coding a video unit, enhancing coding efficiency and effectiveness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional video coding technologies (MPEG-2, MPEG-4, AVC, HEVC, VVC) are used, then video compression is achieved, but coding efficiency and effectiveness are insufficient
Solution Approach 1:
The patent implements a history table that stores previously determined CCP model parameters and uses this historical information to guide current CCP model selection. This feedback mechanism allows the system to learn from past coding decisions and improve subsequent coding efficiency while maintaining effectiveness through adaptive model selection based on historical performance patterns.
Solution Approach 2:
The patent performs preliminary determination of CCP model parameters by maintaining a history table that is updated before or after coding video units. This preliminary action prepares the system with pre-computed model information, enabling faster and more effective coding decisions in subsequent operations without compromising coding effectiveness.
2Reliability
If cross-component prediction models are updated frequently, then coding effectiveness improves, but computational complexity increases
Solution Approach 1:
The patent updates the history table of CCP models periodically - specifically before or after coding each video unit - rather than continuously. This periodic update strategy maintains coding effectiveness by ensuring models are current, while avoiding excessive computational complexity by limiting updates to specific intervals rather than every processing step.
Solution Approach 2:
The system maintains its own history table internally and performs self-updating of CCP models based on its own coding experience. This self-service approach allows the system to improve its own effectiveness without requiring external intervention or complex external control mechanisms, thereby reducing overall system complexity while maintaining high coding effectiveness.
Data Source
AI summary
Embodiments of the present disclosure provide a solution for video processing. A method for video processing is proposed. In the method, for a conversion between a current video block of a video and a bitstream of the video, at least one cross component prediction (CCP) model for the current video block is determined based on at least one history table (HT) of CCP models. The conversion is performed based on the at least one CCP model. The at least one history table of CCP models is updated before or after coding a video unit.


