Neural Network Video Filtering for Luma-Chroma Coding Efficiency
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Solution Overview
Problem
Existing video coding technologies, such as MPEG-2, MPEG-4, ITU-T.263, ITU-T.264/MPEG-4 AVC, and ITU-T.265 HEVC, require improvements in coding efficiency.
Innovation Solution
Implementing a neural network-based filter that processes both luma and chroma components, with signaling of filter usage information in the bitstream, allowing flexible usage and enhancing coding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a neural network-based filter is implemented to process both luma and chroma components, then coding efficiency is improved, but device complexity increases
Solution Approach 1:
The patent implements dynamic control of the neural network-based filter through multiple indication mechanisms in the bitstream. The filter can be selectively applied to different video units, components (luma/chroma), and regions based on coded indications, allowing the system to adapt its complexity level according to content requirements rather than operating at fixed maximum complexity
Solution Approach 2:
The patent applies the neural network filter selectively to specific regions, components, and video units rather than uniformly across the entire video stream. Different indication syntaxes allow the filter to be enabled or disabled for specific luma/chroma components, video units, or regions, optimizing the balance between coding efficiency improvement and device complexity based on local content characteristics
2Adaptability or versatility
If flexible usage of the neural network-based filter is enabled through multiple indication syntaxes, then adaptability is improved, but device complexity increases
Solution Approach 1:
The patent segments the control mechanism into multiple distinct indication syntaxes that can be independently configured. Different syntaxes (e.g., first indication, second indication, third indication) allow separate control over different aspects of filter application (component selection, region selection, video unit selection), enabling fine-grained adaptability while maintaining clear modular control structures
Solution Approach 2:
The patent creates a universal control framework where a single neural network-based filter can serve multiple functions through different indication mechanisms. The same filter infrastructure can be applied to luma components, chroma components, different video units, and different regions, with a unified set of indication syntaxes providing multi-functional control without requiring separate filter instances
Data Source
AI summary
Embodiments of the present disclosure provide a solution for video processing. A method for video processing is proposed. The method comprises: performing a conversion between a current video unit of a video and a bitstream of the video, wherein the bitstream comprises at least one indication indicating first information regarding a usage of a neural network (NN) based filter for the current video unit, and the NN-based filter is configured to process a luma component and a chroma component of the current video unit.