Encoder Merge Candidate Reuse for Sub-Block Uni-Prediction
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Solution Overview
Problem
Existing video coding technologies face challenges in efficiently compressing video data without sacrificing picture quality, particularly in scenarios with limited network bandwidth or storage resources, necessitating improved compression techniques that enhance the compression ratio while maintaining image quality.
Innovation Solution
The method involves constructing a first list based on motion information of neighboring blocks and using it to generate uni-prediction candidates for inter prediction, allowing for sub-block partitioning with regular merge candidate lists without additional motion vector pruning, and selecting L0 or L1 motion vectors based on merge index parity for sub-block prediction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If separate uni-prediction candidate lists are constructed for sub-block prediction, then prediction accuracy is improved, but device complexity and processing overhead increase
Solution Approach 1:
The patent merges the uni-prediction candidate list construction into the existing merge candidate list by reusing motion vectors from bi-prediction candidates. Instead of maintaining separate lists for uni-prediction and bi-prediction, the invention combines both functions into a single merged list that can serve both prediction modes, thereby reducing device complexity while maintaining prediction accuracy.
Solution Approach 2:
The merged candidate list serves multiple functions: it provides candidates for both uni-prediction and bi-prediction modes, and can be used for both full-block and sub-block predictions. This multi-functionality eliminates the need for separate candidate lists and reduces processing overhead while maintaining the accuracy benefits of dedicated uni-prediction lists.
2Productivity
If explicit uni-prediction lists are generated for sub-block prediction, then compression ratio is improved, but processing time and complexity increase
Solution Approach 1:
The patent performs preliminary action by constructing the merged candidate list in advance during the merge candidate list construction phase, before sub-block prediction is performed. This pre-computation allows the list to be reused for both full-block and sub-block predictions, improving compression ratio without incurring additional processing time during the actual prediction stage.
Solution Approach 2:
By merging uni-prediction and bi-prediction candidates into a single list that is constructed once and reused, the invention achieves the compression benefits of explicit uni-prediction lists without the repeated processing overhead of generating separate lists for each prediction operation.
3Measurement precision
If motion vector pruning is applied for sub-block prediction, then prediction accuracy is improved, but device complexity increases
Solution Approach 1:
The merged candidate list is self-sufficient and does not require additional motion vector pruning operations. By carefully selecting and merging candidates from both uni-prediction and bi-prediction sources, the list inherently contains high-quality candidates that do not need further filtering or pruning, thereby maintaining prediction accuracy while reducing device complexity.
Data Source
AI summary
The present disclosure provides methods and devices of processing a block according to a merge candidate list, the method comprising: constructing a first list according to motion information of neighboring blocks of a current block; obtaining prediction information of the current block; when the prediction information of the current block indicates that a sub-block prediction is applied to the current block, obtaining a uni-prediction candidate for the current block according to the first list; using, the uni-prediction candidate for the current block to perform inter prediction of the current block. According to embodiment of the present disclosure, the regular merge list can be directly used and there is no need to explicitly generate the uni-prediction merge candidate list for sub-block prediction.