Cross-Component Video Coding for Lower Luma-Chroma Reconstruction Error
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Solution Overview
Problem
Existing video coding technologies face challenges in reducing reconstruction errors, particularly in the transition between luma and chroma components, which can lead to artifacts and degrade video quality.
Innovation Solution
Implementing cross-component filtering techniques that utilize cross-component filter coefficients to modify reconstructed luma sample data based on chroma sample data, thereby reducing reconstruction errors and improving video quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional video coding techniques are used, then coding efficiency is maintained, but reconstruction error increases and video quality degrades
Solution Approach 1:
The patent merges luma and chroma component processing by applying cross-component filtering that uses both luma and chroma reconstructed samples to filter the luma component. This integration allows the system to leverage correlations between different color spaces to reduce reconstruction error while maintaining coding efficiency through unified processing of multiple components.
Solution Approach 2:
The patent introduces cross-component filter coefficients as an intermediary mechanism that mediates between luma and chroma components. These coefficients, derived from chroma residuals, are applied to luma reconstructed samples to reduce reconstruction error without directly processing chroma data, thus maintaining efficiency while improving accuracy.
2Manufacturing precision
If luma and chroma components are processed independently, then processing simplicity is maintained, but reconstruction error increases at component transitions
Solution Approach 1:
The patent applies local quality by deriving cross-component filter coefficients specifically at regions where luma and chroma components are present and where reconstruction error is detected. The filtering operation is applied selectively based on local characteristics such as residual magnitude and component presence, rather than uniformly across the entire image, thus improving accuracy where needed while maintaining simplicity where not required.
Solution Approach 2:
The patent introduces dynamic adaptability by adjusting the filtering process based on local conditions. The cross-component filter coefficients are dynamically derived from chroma residuals at each location, and the filtering operation is conditionally applied based on detected reconstruction error and component characteristics, allowing the system to adapt its complexity to local requirements.
3Manufacturing precision
If cross-component filtering is applied, then reconstruction error is reduced, but processing time increases
Solution Approach 1:
The patent applies partial action by implementing cross-component filtering only where necessary - specifically at locations where both luma and chroma components are present and where reconstruction error is detected above a threshold. The filtering operation is selectively applied to reduce error in critical regions while skipping processing in regions where the benefit is minimal, thus balancing accuracy improvement with time consumption.
Solution Approach 2:
The patent changes processing parameters dynamically based on local conditions. The strength and application of cross-component filtering are adjusted according to detected reconstruction error magnitude, component presence, and residual characteristics. This parameter adaptation allows the system to optimize between processing time and reconstruction accuracy by applying stronger filtering where needed and weaker or no filtering where time is more critical than precision.
Data Source
AI summary
A video coding device may be configured to perform video coding according to one or more of the techniques described herein.