Motion Candidate List Refinement for Efficient Video Coding
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Solution Overview
Problem
Existing video coding technologies face challenges in achieving high coding efficiency, particularly in the management and optimization of motion candidate lists during video encoding and decoding processes.
Innovation Solution
The proposed methods involve reordering and refining motion candidate lists using refined motion information, updating motion candidate lists by removing redundant candidates, and applying adaptive decoder-side motion vector refinement to improve coding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If motion candidate lists are refined and reordered using refined motion information, then coding efficiency is improved, but computational complexity increases
Solution Approach 1:
The patent applies preliminary action by performing motion candidate refinement and reordering operations before the actual video block encoding/decoding process. The motion candidate list is refined using DMVR (Decoder-side Motion Vector Refinement) to obtain more accurate motion vectors, and then reordered based on prediction accuracy metrics calculated in advance. This preliminary preparation of high-quality motion candidates improves subsequent coding efficiency without adding complexity during the main encoding/decoding flow.
Solution Approach 2:
The patent changes parameters by introducing refined motion vector precision through DMVR and using cost values (prediction accuracy metrics) as reordering criteria. Instead of using conventional motion candidates with standard precision, the system transforms the motion candidate parameters to include refined motion vectors with higher precision (e.g., 1/16 pixel accuracy) and reorders them based on calculated cost values that reflect prediction accuracy, thereby improving coding efficiency.
2Productivity
If redundant motion candidates are removed from motion candidate lists, then coding efficiency improves, but the complexity of candidate selection increases
Solution Approach 1:
The patent applies the extraction principle by removing redundant motion candidates from the motion candidate list. Specifically, after refining motion candidates using DMVR, the system identifies and extracts (removes) candidates that are redundant or less optimal based on calculated cost values. This extraction of redundant elements reduces the effective size of the candidate list while maintaining or improving coding efficiency, as only the most promising candidates are retained for subsequent encoding/decoding operations.
3Manufacturing precision
If adaptive decoder-side motion vector refinement is applied, then coding gain increases, but processing time increases
Solution Approach 1:
The patent applies partial action by selectively applying DMVR (Decoder-side Motion Vector Refinement) only to specific motion candidates that benefit most from refinement, rather than uniformly refining all candidates. The system calculates cost values to identify which candidates warrant refinement and focuses computational resources on those partial cases. This selective approach achieves significant coding gain while limiting the increase in processing time to only the necessary portions.
Data Source
AI summary
Embodiments of the present disclosure provide a solution for video processing. A method for video processing is proposed. The method comprises: applying, during a conversion between a target block of a video and a bitstream of the target block, a processing procedure to at least one motion candidate in a motion candidate list; reordering the motion candidate list by applying a first reordering process to the motion candidate list after the processing procedure; and performing the conversion based on the reordered motion candidate list.