Motion Vector Candidate Reordering for Efficient Inter Prediction
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Solution Overview
Problem
Existing image encoding/decoding technologies face challenges in improving coding efficiency, particularly in the correction of motion information during inter-prediction processes.
Innovation Solution
The proposed solution involves generating a list of motion information candidates using initial motion information, applying corrections through template matching and/or bilateral matching, and reordering these candidates based on costs to determine final motion information for improved prediction blocks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If motion information correction is applied through template matching and bilateral matching, then coding efficiency is improved, but computational complexity increases
Solution Approach 1:
The patent applies preliminary action by generating a list of motion information candidates before final selection. The motion information correction process (template matching, bilateral matching) is performed in advance to create multiple candidates, which are then reordered based on costs. This preliminary correction and candidate generation resolves the contradiction by preparing optimized motion information upfront, improving coding efficiency while managing computational complexity through structured candidate management.
2Measurement precision
If multiple motion information candidates are generated and reordered based on costs, then prediction accuracy is improved, but processing time increases
Solution Approach 1:
The patent applies parameter changes by reordering motion information candidates based on cost parameters. Different candidates are evaluated using cost metrics, and their arrangement is changed according to these costs. This parameter-based reordering improves prediction accuracy by selecting better motion information candidates while managing processing time through efficient cost-based sorting rather than exhaustive evaluation.
3Manufacturing precision
If motion information is corrected using template matching and bilateral matching, then image quality is improved, but encoding complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the motion information correction process into distinct stages: template matching is performed separately from bilateral matching, and each produces intermediate results that are combined. The motion information candidates are segmented into multiple options that are then evaluated and reordered. This segmented approach improves image quality through comprehensive correction while managing encoding complexity by breaking down the overall process into manageable, sequential steps.
Data Source
AI summary
Disclosed herein are a method, an apparatus and a storage medium for image encoding/decoding. When initial motion information for a target block is determined, a list is generated based on the initial motion information. Motion information for the target block is determined using candidates in the list. Motion information or final motion information generated by correction of the motion information is used to generate a prediction block for the target block. Some of candidates in the list may be selected based on costs of the candidates. Various methods are used to determine costs of candidates and perform selection based on the costs.