Inter-Prediction Candidate List Updating for Image Compression
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Solution Overview
Problem
High-resolution and high-quality image data requires high-efficiency encoding/decoding techniques to reduce the increased data volume, leading to higher transmission and storage costs.
Innovation Solution
The method involves deriving a candidate list for inter-prediction, using a cumulative coding information candidate list to improve compression efficiency by updating the candidate list for inter-prediction of blocks, and utilizing a coding information buffer to enhance encoding/decoding processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If high-resolution and high-quality image data is used, then image quality is improved, but data volume increases leading to higher transmission and storage costs
Solution Approach 1:
The patent segments the image processing into coding tree units (CTUs) and further into coding blocks, allowing independent processing and prediction. This segmentation enables efficient inter-prediction by deriving motion information from specific blocks and updating candidate lists locally, reducing the overall data volume while maintaining quality through targeted compression techniques.
Solution Approach 2:
The patent performs preliminary actions by deriving motion information for coding blocks before actual prediction occurs. Motion information is derived in advance and stored in candidate lists, which are then used for inter-prediction of subsequent blocks. This preliminary derivation of motion vectors and updating of candidate lists enables efficient compression by preparing prediction data beforehand.
2Productivity
If conventional encoding techniques are used, then processing is simple, but compression efficiency is insufficient for high-resolution images
Solution Approach 1:
The patent implements dynamic candidate list updating where the candidate list for inter-prediction is modified based on previously derived motion information. The list is updated by inserting new motion information and removing old entries, allowing the system to adapt to different image content dynamically. This dynamic adjustment optimizes compression efficiency without requiring overly complex fixed structures.
Solution Approach 2:
The patent incorporates feedback mechanisms where motion information derived from previously processed coding blocks is fed back into the candidate list for subsequent blocks. The cumulative coding information candidate list uses previously encoded motion data to improve prediction accuracy for current and future blocks, creating a feedback loop that enhances compression efficiency progressively.
Data Source
AI summary
An image decoding method is disclosed in the present specification. An image decoding method according to the present invention may comprise deriving a candidate list for inter-prediction of a current block, deriving motion information of the current block by using the candidate list, deriving a cumulative coding information candidate by using the motion information of the current block, inserting the derived cumulative coding information candidate into a cumulative coding information candidate list and updating the candidate list by using the cumulative coding information candidate list, wherein the updated candidate list is used for inter-prediction of a block to be decoded after the current block.