Merge-Candidate Motion Vector Offsets for Inter Prediction
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Solution Overview
Problem
The increasing data volume of high-definition video services poses a challenge for efficient video compression, as existing standards like HEVC are reaching their performance limits.
Innovation Solution
A method is introduced to refine motion vectors using offset vectors in video encoding and decoding, with adaptive determination of magnitude and direction based on index information, and signaling these vectors through picture parameter sets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If motion vector refinement using offset vectors is implemented, then inter prediction efficiency is improved, but device complexity increases
Solution Approach 1:
The motion vector refinement process is segmented into distinct components: merge candidate selection, offset vector derivation, and motion vector calculation. This segmentation allows complex operations to be broken down into manageable steps, improving implementation clarity while maintaining prediction efficiency through structured processing of motion information
Solution Approach 2:
The system dynamically determines motion vector refinement based on merge candidate selection and offset vector calculation. The process adapts to different video content characteristics by selecting appropriate merge candidates and computing corresponding offset vectors, enabling flexible motion prediction that balances complexity with prediction accuracy
2Measurement precision
If adaptive offset vector determination is used, then motion vector accuracy is improved, but signaling overhead increases
Solution Approach 1:
The system changes parameters such as motion magnitude candidates and motion direction candidates based on the selected merge candidate. By dynamically adjusting these parameters according to the specific merge candidate used, the system achieves accurate motion vector refinement while controlling the amount of signaling information required to describe the refinement process
Data Source
AI summary
A video decoding method according to the present disclosure includes the steps that: a merge candidate list for a current block is generated; a merge candidate for the current block is determined among merge candidates included in the merge candidate list; an offset vector for the current block is derived; and a motion vector for the current block is derived by adding the offset vector to a motion vector of the merge candidate.