Bilateral Filtering Before Chroma Subsampling in Video Coding
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Solution Overview
Problem
Existing video coding technologies face challenges in efficiently handling chroma subsampling and intra prediction modes, leading to inefficiencies in bandwidth usage and video quality, particularly in advanced codecs like VVC.
Innovation Solution
The implementation of bilateral filtering (BF) processes, including average, weighted, and Wiener functions, to enhance video data processing, combined with adaptive BF techniques, to improve video coding efficiency and quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If chroma subsampling is applied to reduce bandwidth, then bandwidth usage is reduced, but video quality deteriorates
Solution Approach 1:
The bilateral filter is applied before chroma subsampling to pre-process the chroma samples, enhancing their quality in advance. This preliminary filtering reduces noise and artifacts that would otherwise be amplified by subsampling, thereby maintaining video quality while still achieving bandwidth reduction through subsampling.
Solution Approach 2:
The bilateral filter acts as an intermediary between the original chroma samples and the subsampled chroma data. It processes the chroma samples to preserve important visual information while reducing noise, serving as a mediator that allows both bandwidth reduction and quality preservation to coexist.
2Manufacturing precision
If bilateral filtering is applied to enhance video quality, then video quality is improved, but computational complexity increases
Solution Approach 1:
The bilateral filter is applied selectively to chroma samples rather than all video data. By focusing the computational effort only on chroma subsampling enhancement and using localized filtering windows, the computational complexity is significantly reduced compared to applying full bilateral filtering to the entire video stream.
3Productivity
If adaptive bilateral filtering with online-trained parameters is used, then video coding efficiency is improved, but processing time increases
Solution Approach 1:
Filter parameters are pre-trained offline using training video sequences, creating lookup tables of optimal parameters. During actual video coding, these pre-computed parameters are directly applied without real-time training, significantly reducing processing time while maintaining the coding efficiency benefits of adaptive filtering.
Data Source
AI summary
A mechanism for processing video data is disclosed. The mechanism includes determining to apply a bilateral filter (BF) process to samples of a picture, wherein the BF process applies an average sum, a weighted sum, a linear sum, a non-linear sum, a Wiener function, or combinations thereof. A conversion is performed between a visual media data and a bitstream based on the BF process.