Neural-Network Post-Filter SEI Message Ordering in Video Decoding
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Solution Overview
Problem
Existing video coding technologies face challenges in efficiently managing and decoding neural-network post-filter activation (NNPFA) and characteristics (NNPFC) Supplemental Enhancement Information (SEI) messages, leading to potential errors and inefficiencies in video processing.
Innovation Solution
The proposed solution involves a method for processing media data that ensures a neural-network post-filter activation (NNPFA) SEI message with a specific identifier is only present in a Picture Unit (PU) if certain conditions are met, such as the presence of a corresponding NNPFC SEI message in the current or preceding PU, thereby maintaining correct ordering and presence of these messages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If NNPFA SEI messages are allowed to be present without strict conditions, then the flexibility and adaptability of the video processing system is improved, but the reliability and accuracy of message association deteriorates due to potential meaningless or misplaced messages
Solution Approach 1:
The patent applies preliminary action by requiring that NNPFC SEI messages be present and processed before NNPFA SEI messages in decoding order. This preliminary establishment of filter characteristics ensures that when activation messages are received, the associated filter parameters are already defined and valid, preventing meaningless or misplaced messages while maintaining system flexibility
2Reliability
If strict conditions are imposed on the presence and ordering of SEI messages, then the reliability and accuracy of video decoding is improved, but the device complexity and difficulty of implementation increases
Solution Approach 1:
The patent inverts the conventional approach by making the presence of NNPFA messages conditional upon the prior presence of NNPFC messages, rather than allowing all messages freely and validating them later. This inversion of the message presence logic simplifies the decoding process by preventing invalid message combinations at the source, reducing implementation complexity while maintaining high reliability
3Ease of operation
If NNPFA SEI messages are freely present in any PU, then the ease of operation and simplicity of encoding is improved, but the loss of information and potential for decoding errors increases
Solution Approach 1:
The patent implements feedback by establishing a dependency relationship where the validity of NNPFA SEI messages is determined by the prior presence of corresponding NNPFC SEI messages. This feedback mechanism ensures that activation messages only appear when their associated filter characteristics have been properly defined, preventing information loss and decoding errors while maintaining encoding simplicity
Data Source
AI summary
A mechanism for processing video data is disclosed. The mechanism includes performing a conversion between a visual media data and a bitstream based on a rule. The rule specifies that a neural-network post-filter activation (NNPFA) Supplemental Enhancement Information (SEI) message with a first particular value of an NNPFA identifier is only present in a current Picture Unit (PU) when one or both of the following conditions are met. First, a current Coded Layer Video Sequence (CLVS) contains a neural-network post-filter characteristics (NNPFC) SEI message with a NNPFC identifier (nnpfc_id) equal to the first particular value of the NNPFA identifier in a preceding PU that precedes the current PU in decoding order. Second, an NNPFC SEI message with nnpfc_id equal to the first particular value of the NNPFA identifier is contained in the current PU.