Bilateral Filter Side Information for Artifact-Reduced Video Coding
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Solution Overview
Problem
Existing video coding technologies face challenges in efficiently managing bandwidth demand and compression efficiency, particularly in handling chroma subsampling and in-loop filtering processes, which can lead to artifacts and increased data rates.
Innovation Solution
The use of side information as input to filters, such as bilateral and Hadamard transform domain filters, for processing video data and converting between visual media data and bitstreams, along with adaptive loop filtering to minimize mean square errors and improve coding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If chroma subsampling is applied to reduce bandwidth, then data rate is reduced, but video quality and color accuracy deteriorate
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the chroma subsampling factor based on content characteristics and encoding conditions. Instead of using fixed subsampling ratios, the encoder can select between different subsampling modes (e.g., 4:4:4, 4:2:2, 4:2:0) or adjust the subsampling strength to balance bandwidth reduction with quality preservation.
Solution Approach 2:
The patent introduces dynamic adaptation in the encoding process where chroma subsampling parameters are adjusted based on scene complexity, motion characteristics, and importance regions. This allows the system to maintain high quality in critical areas while achieving compression in less important regions, resolving the contradiction between data rate reduction and quality preservation.
2Manufacturing precision
If in-loop filtering is applied to improve video quality, then artifacts are reduced, but computational complexity and processing time increase
Solution Approach 1:
The patent segments the video content into different regions or blocks and applies filtering selectively rather than uniformly across the entire frame. By dividing the processing into smaller units and applying filters only where needed (e.g., at block boundaries or in regions with artifacts), the computational complexity is significantly reduced while maintaining quality improvement benefits.
Solution Approach 2:
The patent implements local quality enhancement by applying different filtering strengths or types to different regions of the video based on local characteristics. Areas with severe artifacts receive stronger filtering, while regions with good quality or important details receive minimal or no filtering, thus improving overall quality without uniformly increasing computational burden.
3Manufacturing precision
If stronger filtering is applied to remove artifacts, then video quality improves, but bandwidth and data rates increase
Solution Approach 1:
The patent applies partial filtering action by selectively removing only the most harmful artifacts rather than applying full-strength filtering across all regions. This approach targets specific artifact types or locations that have the greatest impact on perceived quality, achieving satisfactory video quality with reduced filtering intensity and corresponding bandwidth consumption.
Data Source
AI summary
A mechanism for processing video data is disclosed. The mechanism includes determining to employ side information as input to a filter. The filter can be a bilateral filter (BF) or a Hadamard transform domain filter (HTDF). A conversion is performed between a visual media data and a bitstream based on the filter.