Application-Specific Neural Network Post-Filter Signaling in Video Coding
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Solution Overview
Problem
Existing video coding standards lack efficient mechanisms for incorporating neural network post-filters, limiting the ability to adapt filtering processes to specific application purposes.
Innovation Solution
Incorporating a neural network post-filter characteristics message with syntax elements indicating the application-specific purpose and a universal resource identifier, enabling dynamic adaptation of filtering processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing video coding standards are used without neural network post-filter integration, then the coding process remains simple and compatible, but the ability to adapt filtering processes to specific application purposes is limited
Solution Approach 1:
The patent segments the video coding system by introducing a separate neural network post-filter module that operates independently after the main decoding process. This allows the filtering adaptation functionality to be added without modifying the core video coding standard, thus improving adaptability while maintaining relative simplicity of the base system.
Solution Approach 2:
The patent introduces syntax elements and signaling mechanisms as intermediaries between the video bitstream and the neural network post-filter. These intermediaries carry application-specific purpose information that enables the filter to adapt its behavior without requiring direct integration into the core coding standard, thereby balancing adaptability with system complexity.
2Manufacturing precision
If neural network post-filters are integrated with application-specific purpose information, then video quality and adaptability are enhanced, but the complexity of signaling and processing increases
Solution Approach 1:
The patent applies local quality by introducing application-specific purpose information at specific locations in the bitstream (through syntax elements in parameter sets or picture headers) rather than uniformly across the entire system. This allows video quality enhancement to be applied selectively where needed, while keeping the signaling complexity localized and manageable.
Solution Approach 2:
The patent uses parameter changes by introducing syntax elements that convey application-specific purpose information, which then modify the behavior parameters of the neural network post-filter. This allows the filter to adapt its processing characteristics based on the signaled parameters, improving video quality for specific applications without requiring a completely different system architecture.
3Adaptability or versatility
If comprehensive application-specific information is signaled in the bitstream, then the neural network post-filter can be precisely optimized for specific purposes, but the bitstream size and processing overhead increase
Solution Approach 1:
The patent achieves universality by designing syntax elements that can convey multiple types of application-specific information through a unified signaling mechanism. The same syntax element structure can indicate different application purposes (e.g., surveillance, streaming, storage) and the neural network filter can adapt its behavior accordingly, providing precise optimization for specific purposes without requiring separate signaling systems for each application, thus avoiding excessive bitstream expansion.
Data Source
AI summary
A device may be configured to perform filtering based on information included in a neural network post-filter characteristics message. In one example, the neural network post-filter characteristics message includes a syntax element indicating whether a purpose of a neural network post-filter is specified by an application. In one example, the neural network post-filter characteristics message includes a syntax element specifying a universal resource identifier indicating an application specified purpose.