NNPFC SEI Message Repetition for Consistent Image Decoding
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Solution Overview
Problem
The increasing demand for high-resolution and high-quality images leads to higher transmission and storage costs due to increased bit rates, necessitating improved image encoding/decoding efficiency.
Innovation Solution
An image encoding/decoding method that allows for the repetition of a neural-network post-filter characteristics (NNPFC) supplemental enhancement information (SEI) message with the same filter identification information, ensuring consistent decoding order and improved efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If high-resolution and high-quality image data is transmitted, then image quality is improved, but transmission costs and storage costs increase
Solution Approach 1:
The patent uses neural network post-processing filters to generate reconstructed image data that copies the essential visual information of the original high-resolution image. By applying learned filtering operations to the decoded image data, the system creates a high-quality copy that approximates the original image quality without requiring transmission of the full original data stream.
2Stability of the object's composition
If neural-network post-filter characteristics SEI message is repeated with same filter identification, then decoding consistency is improved, but message redundancy increases
Solution Approach 1:
The patent applies preliminary action by establishing the neural network post-filter characteristics through an initial NNPFC SEI message, then repeating this message with the same filter identification information to maintain consistency. The repetition serves as a preliminary confirmation that ensures the decoder applies the correct filter characteristics without requiring complete re-transmission of all filter parameters.
Solution Approach 2:
The repeated NNPFC SEI message with identical filter identification information serves multiple functions: it confirms the filter characteristics to the decoder, maintains consistency across different decoding scenarios, and provides a universal mechanism for ensuring reliable post-processing filter application throughout the decoded video sequence.
Data Source
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AI summary
Provided are an image encoding/decoding method, a bitstream transmission method, and a computer-readable recording medium for storing a bitstream. The image decoding method according to the present disclosure may comprise the steps of: receiving a neural-network post-filter (NNPF)-related supplemental enhancement information (SEI) message to be applied to the current picture; reconstructing NNPF-related information on the basis of the NNPF-related SEI message; and on the basis of the NNPF-related information, applying an NNPF to the current picture. The NNPF-related SEI message includes a neural-network post-filter characteristics (NNPFC) SEI message including filter identification information and filter property present information, and on the basis that the NNPFC SEI message includes a base NNPF, the filter property present information may be limited to have a first value indicating that filter properties are present.