ALF Adaptation Parameter Selection for Fuller Historical Candidate Sets
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Solution Overview
Problem
The current Adaptive Loop Filter (ALF) technology in H.266/Versatile Video Coding (VVC) has suboptimal decision factors, leading to a large number of luma ALF APSs being explicitly transmitted while chroma ALF APSs are absent, resulting in a low fullness of historical candidate sets.
Innovation Solution
A filtering parameter processing method that determines a new APS of a current filtering mode, corrects the decision factor, and updates historical filtering parameters to enhance the use of new APSs, thereby increasing the fullness of historical candidate sets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the current ALF decision factors are used independently for each filtering mode, then the decision process is simple and fast, but the fullness of historical candidate sets becomes low due to excessive luma ALF APS transmission and absent chroma ALF APS
Solution Approach 1:
The patent merges the decision processes for different filtering modes (luma ALF, chroma ALF, CCALF Cb, CCALF Cr) into a unified decision framework. By combining the decision factors and using a shared historical candidate set across all filtering modes, the system achieves both efficient decision-making and fullness of historical candidate sets, resolving the contradiction between processing speed and data completeness.
2Ease of manufacture
If luma ALF APS is prioritized in the decision process, then the decision factor calculation is simplified, but the chroma ALF APS and other filtering modes are neglected resulting in empty historical candidate sets
Solution Approach 1:
The patent creates a universal decision framework that applies to all filtering modes (luma ALF, chroma ALF, CCALF Cb, CCALF Cr) simultaneously. The unified decision factors and shared historical candidate set structure enable the system to handle multiple filtering modes with equal importance, achieving both calculation simplicity and comprehensive coverage without requiring separate decision processes for each mode.
Data Source
AI summary
Provided are a filtering parameter processing method, a device, and a storage medium. The method includes: determining a new adaptation parameter set (APS) of a current filtering mode of a target filtering unit; after determining that the current filtering mode satisfies a decision factor correction condition, determining a corrected decision factor, where the corrected decision factor is less than a decision factor before correction; and determining, according to the corrected decision factor, whether to use the new APS of the current filtering mode.


