Cross-plane filtering for chroma signal enhancement
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Solution Overview
Problem
Existing video coding systems using known chroma prediction techniques often result in video images with significantly blurred edges and textures in the chroma planes.
Innovation Solution
The implementation of cross-plane filtering, which uses adaptive filters to restore blurred edges and textures in the chroma planes by leveraging information from the corresponding luma plane, while minimizing overhead in the bitstream.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If cross-plane filtering is applied to restore blurred edges and textures in chroma planes, then chroma plane quality is improved, but bitstream overhead increases
Solution Approach 1:
The patent applies parameter changes by adapting filter coefficients based on chroma block characteristics. Different filter coefficients are selected or generated depending on the chroma block's properties (e.g., edge detection results, texture analysis), allowing the system to optimize filtering strength and type dynamically. This resolves the contradiction by applying strong filtering only where needed while using weaker or no filtering elsewhere, thus improving quality where possible without unnecessarily increasing overhead.
Solution Approach 2:
The system dynamically adjusts filtering operations based on real-time analysis of chroma block characteristics. The filter application is not static but adapts to local image content, switching between different filter types and strengths based on detected edges, textures, and block properties. This dynamic approach ensures that filtering overhead is minimized while maintaining high quality where chroma details are present.
2Measurement precision
If adaptive cross-plane filters are used to enhance chroma planes, then prediction accuracy is improved, but device complexity increases
Solution Approach 1:
The patent segments the chroma plane processing into distinct blocks and applies different filtering strategies to different segments based on their characteristics. By dividing the image into chroma blocks and analyzing each block's properties (edges, textures, smoothness), the system can apply appropriate filters selectively rather than uniformly. This segmentation reduces overall complexity by avoiding unnecessary filtering operations in homogeneous regions while maintaining high prediction accuracy in complex regions.
Solution Approach 2:
The system implements local quality by applying different filter characteristics to different regions of the chroma plane based on local analysis. Regions with edges and textures receive stronger filtering, while smooth regions receive weaker or no filtering. This localized approach improves prediction accuracy where needed without subjecting the entire image to complex processing, thus reducing overall device complexity.
Data Source
AI summary
Cross-plane filtering may be used to restore blurred edges and/or textures in one or both chroma planes using information from a corresponding luma plane. Adaptive cross-plane filters may be implemented. Cross-plane filter coefficients may be quantized and/or signaled such that overhead in a bitstream minimizes performance degradation. Cross-plane filtering may be applied to select regions of a video image (e.g., to edge areas). Cross-plane filters may be implemented in single-layer video coding systems and/or multi-layer video coding systems.