Neural Network Post-Filter Signaling for Application-Specific Video Coding
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Solution Overview
Problem
Existing video coding standards lack efficient mechanisms for signaling neural network post-filter parameter information, which is crucial for enhancing video quality post-decoding.
Innovation Solution
Incorporating techniques for signaling neural network post-filter parameter information through syntax elements, including conditional signaling of a universal resource identifier, to facilitate application-specific purposes in video coding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If neural network post-filter parameter information is signaled in video coding, then video quality is improved, but bitstream complexity increases
Solution Approach 1:
The patent applies local quality by differentiating the signaling approach based on the specific application purpose. Different syntax elements are used to indicate different purposes (e.g., upscaling, deblocking, denoising), allowing the bitstream to carry only the necessary information for each specific case rather than all possible parameters universally.
Solution Approach 2:
The patent introduces dynamic signaling where the inclusion of certain syntax elements (like application-specific purpose identifiers) is conditional based on whether the purpose is pre-defined or custom. This allows the bitstream structure to adapt dynamically - using simpler signaling when standard purposes apply and more detailed signaling only when needed.
2Adaptability or versatility
If application-specific purpose information is included in the bitstream, then adaptability is improved, but data transmission volume increases
Solution Approach 1:
The patent creates a universal signaling framework that handles multiple application purposes through a common syntax structure. The same syntax elements can represent different purposes (upscaling, deblocking, denoising, etc.), allowing one signaling mechanism to serve multiple functions rather than requiring separate mechanisms for each application.
Solution Approach 2:
The patent extracts only the essential purpose identification information from the full application-specific parameters. Rather than transmitting complete application configurations, it signals condensed purpose identifiers that reference pre-defined or registered applications, removing unnecessary data while preserving adaptability.
3Measurement precision
If neural network post-filter parameters are signaled, then decoding accuracy is improved, but processing overhead increases
Solution Approach 1:
The patent applies preliminary action by establishing a registry or pre-definition of common application purposes before the actual video decoding process. When a purpose is pre-defined, the system can use compact reference identifiers rather than transmitting full parameter sets, reducing processing overhead while maintaining decoding accuracy for standard cases.
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. In one example, the neural network post-filter characteristics message includes a syntax element specifying whether the syntax element specifying a universal resource identifier indicating an application specified purpose is present.