Multiple-Hypothesis Video Prediction With Boundary Matching
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Solution Overview
Problem
Existing video coding systems, such as VVC, face challenges in efficiently handling complex motion patterns and inter-prediction processes, leading to increased computational complexity and reduced coding efficiency.
Innovation Solution
The implementation of advanced inter-prediction tools in VVC, including extended merge prediction, affine motion compensation, and adaptive motion vector resolution, to enhance coding efficiency by optimizing motion parameter signaling and prediction processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If advanced inter-prediction tools are implemented, then coding efficiency is improved, but computational complexity increases
Solution Approach 1:
The patent segments the prediction process by dividing the current block into multiple sub-blocks and generating separate prediction candidates for each sub-block. This segmentation allows the system to handle complex motion patterns locally while maintaining overall computational manageability through distributed processing across multiple regions.
Solution Approach 2:
The patent implements dynamic adaptation by conditionally applying different prediction tools and parameters based on block characteristics. The system dynamically selects between various motion compensation methods and adjusts motion vector precision according to the specific content and motion complexity of each block, optimizing the balance between coding efficiency and computational load.
2Productivity
If motion parameter signaling is optimized, then coding efficiency is improved, but measurement precision requirements increase
Solution Approach 1:
The patent applies different motion parameter precision levels to different regions based on local motion characteristics. High-precision motion vectors are used for blocks with complex or rapid motion, while lower precision is sufficient for static or slowly moving regions. This local quality approach maintains coding efficiency where needed while reducing overall measurement precision requirements.
Solution Approach 2:
The patent implements adaptive parameter changes by adjusting motion vector precision, block size, and prediction tool selection based on measured motion complexity. The system changes parameters dynamically according to the content being encoded, using higher precision only when necessary to maintain coding efficiency while minimizing overall computational and measurement demands.
Data Source
AI summary
A method and apparatus for predictive coding. According to the method, combined prediction members are determined, where each of the combined prediction member includes a weighted sum of a first prediction candidate and a second prediction candidate using a target weighting selected from a weighting set. Boundary matching costs associated with the combined prediction members are determined, where each of the boundary matching costs is determined, for the combined prediction member with the target weighting, by using predicted samples of the current block based on the combined prediction member with the target weighting and neighbouring reconstructed samples of the current block. The current block is then encoded or decoded using a final combined prediction decided based on at least one of the boundary matching costs.