Template-Matched Merge Candidates for Accurate Video Block Coding
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Solution Overview
Problem
Existing video coding technologies face challenges in efficiently populating merge candidate lists, leading to suboptimal coding accuracy and increased signaling overhead, which affects compression efficiency and video quality.
Innovation Solution
Employing template-matching techniques to refine merge candidates and populate merge candidate lists, using motion vectors and block vectors to improve match accuracy and reduce signaling overhead.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional merge candidate list construction methods are used, then the implementation is simple, but the coding accuracy is suboptimal and merge list diversity is limited
Solution Approach 1:
The patent performs preliminary template matching to identify candidate blocks before constructing the merge candidate list. By pre-identifying blocks with similar templates to the current block, the method prepares refined motion vector candidates in advance, improving coding accuracy without significantly increasing overall system complexity.
Solution Approach 2:
The patent changes the parameter selection criteria for merge candidates from traditional spatial/temporal neighboring blocks to blocks selected by template matching similarity. This parameter change allows the system to prioritize blocks with higher template similarity, thereby improving merge list diversity and coding accuracy.
2Measurement precision
If more merge candidates are included in the merge candidate list to improve match accuracy, then the coding accuracy improves, but the signaling overhead increases
Solution Approach 1:
The patent applies local quality by differentiating the treatment of merge candidates based on their template matching characteristics. Blocks with high template similarity receive priority inclusion in the merge candidate list, while less similar blocks are excluded. This selective approach improves match accuracy for relevant blocks without unnecessarily increasing signaling overhead for all possible candidates.
Data Source
AI summary
The various implementations described herein include methods and systems for coding video. In one aspect, a method includes receiving a video bitstream comprising a current picture composed of a plurality of blocks, including a current block. The method also includes identifying a merge candidate for the current block and identifying a refined merge candidate by refining a position of the merge candidate using a template-matching technique. The method further includes identifying a reference vector for the refined merge candidate and populating a merge candidate list for the current block using the reference vector. The method also includes reconstructing the current block using information from the merge candidate list.