Cross-Component Loop Filtering for Chroma Coding Accuracy
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Solution Overview
Problem
The increasing demand for high-resolution and high-quality image/video data, particularly in immersive media formats like VR and AR, leads to higher transmission and storage costs due to the increased amount of information, necessitating a more efficient compression technology.
Innovation Solution
The implementation of Cross-Component Adaptive Loop Filter (CCALF) and adaptive signaling schemes in the image/video coding process, allowing for efficient filtering and encoding/decoding of chroma components based on luma samples, with adaptive application in units of pictures, slices, and coding blocks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If high-resolution and high-quality image/video data is transmitted and stored using existing media and storage systems, then image quality is maintained, but transmission cost and storage cost increase significantly
Solution Approach 1:
The patent applies Cross-Component Adaptive Loop Filtering (CC-ALF) that uses luma sample values to refine chroma component values. By changing the filtering parameters and using adaptive filtering coefficients, the patent improves compression efficiency while maintaining high image quality, thereby reducing transmission and storage costs for high-resolution video data
2Manufacturing precision
If Cross-Component Adaptive Loop Filter is applied to refine chroma components using luma sample values, then visual quality and coding accuracy improve, but device complexity and computational requirements increase
Solution Approach 1:
The patent uses luma sample values as an intermediary to refine chroma component values. Instead of directly processing chroma samples, the filtering process uses the already-processed luma components as a mediator to achieve chroma refinement, which simplifies the overall processing complexity while maintaining coding accuracy
Solution Approach 2:
The patent employs adaptive filtering coefficients that are selected based on local image characteristics. By dynamically changing filtering parameters rather than using fixed coefficients, the system achieves high coding accuracy without requiring overly complex processing, as the adaptivity is achieved through parameter selection rather than complex algorithms
3Manufacturing precision
If CCALF process is applied in all picture units, slices, and coding blocks, then overall picture quality improves, but encoding time and computational load increase
Solution Approach 1:
The patent applies CC-ALF selectively to specific picture units, slices, and coding blocks based on local image characteristics and importance. Rather than uniformly applying filtering to all regions, the system identifies and applies filtering only where it provides the most benefit, thereby improving overall picture quality while reducing total encoding time and computational load
Solution Approach 2:
The patent implements partial application of CC-ALF by using signaling mechanisms to indicate which picture units, slices, or coding blocks should receive filtering. This partial action approach applies filtering only where necessary to achieve acceptable quality levels, avoiding the excessive computational burden of universal application while maintaining sufficient picture quality
Data Source
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AI summary
According to one embodiment of the present document, cross-component filter coefficients for cross-component filtering can be derived. Modified filtered reconstructed chroma samples can be generated on the basis of the cross-component filter coefficients. The present embodiment can improve the accuracy of in-loop filtering.