Neural Network Post-Filter Signaling for Video Bitstream Integration
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Solution Overview
Problem
Existing video coding standards lack efficient methods for signaling neural network post-filter parameter information, which can enhance video quality but are not adequately integrated into current standards like ITU-T H.265, JEM, and JVET-T2001.
Innovation Solution
Incorporating techniques for signaling neural network post-filter characteristics through a dedicated syntax element sequence, where a first syntax element indicates the purpose of the post-processing filter, and a second syntax element specifies the presence of additional syntax elements related to input formatting, output formatting, and complexity, enabling effective integration of neural network post-filters in video coding systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If neural network post-filter parameter information is not signaled in current video coding standards, then the bitstream structure remains simple and compatible with existing decoders, but the ability to utilize advanced post-processing techniques for improving video quality is limited
Solution Approach 1:
The patent segments the bitstream structure by introducing separate syntax elements specifically for neural network post-filter parameters. This includes dividing parameter signaling into distinct components such as filter type identification, parameter presence flags, and actual parameter values, allowing the bitstream to carry enhanced information without fundamentally altering the existing video coding framework.
Solution Approach 2:
The patent changes the parameter space of the bitstream by introducing new syntax elements that carry neural network post-filter specific parameters. These parameters include filter type identifiers, activation flags, and configuration data that enable decoders to apply advanced post-processing while maintaining backward compatibility through optional parameter structures.
2Adaptability or versatility
If neural network post-filter syntax elements are added to the bitstream, then adaptive filtering and quality improvement capabilities are enabled, but the complexity of the video coding system increases
Solution Approach 1:
The patent creates a universal syntax element structure that can accommodate multiple types of neural network post-filters and configuration options through a single standardized interface. The bitstream structure is designed to be multi-functional, supporting various filter types and parameter configurations without requiring separate signaling mechanisms for each case, thereby reducing overall system complexity.
Solution Approach 2:
The patent implements optional parameter structures where only necessary neural network post-filter syntax elements are included in the bitstream based on actual usage requirements. This partial action approach allows the system to gain enhanced post-processing capabilities when needed while maintaining simpler operation when neural network filters are not applied, thus balancing versatility with complexity management.
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 a purpose of a post-processing filter and a syntax element specifying whether syntax elements related to a purpose, input formatting, output formatting, and complexity of the post-processing filter are present in the neural network post-filter characteristics message. The syntax element indicating a purpose may precede the syntax element specifying whether syntax elements are present.