Video Encoding and Decoding with Adaptive Motion Offset Vectors
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Solution Overview
Problem
The increasing data volume associated with high-definition video services poses a challenge for existing video compression technologies, necessitating improved video compression efficiency.
Innovation Solution
A method of refining motion vectors using offset vectors in video encoding and decoding, where the magnitude and direction of the offset vector are determined adaptively based on index information, and signaling methods are employed to optimize video compression.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If HEVC is used to improve video compression rate, then compression performance is improved, but the limitations of HEVC become more apparent as display panels get bigger and video quality requirements increase
Solution Approach 1:
The patent applies parameter changes by introducing an offset vector mechanism that modifies motion vector parameters. The offset vector is derived from motion magnitude candidates and direction candidates, allowing adaptive adjustment of motion vector precision and range. This enables the system to optimize compression parameters dynamically based on video content characteristics, resolving the contradiction between compression rate and quality by finding the optimal parameter setting for each scenario.
Solution Approach 2:
The patent implements dynamics through the adaptive offset vector derivation process. The offset vector magnitude and direction are determined based on motion magnitude candidates and direction candidates that can vary depending on video content. This dynamic adjustment allows the system to adapt motion vector parameters in real-time based on actual video characteristics, improving both compression efficiency and quality reliability.
2Measurement precision
If motion vector precision is increased to improve prediction accuracy, then inter prediction efficiency is improved, but data volume increases
Solution Approach 1:
The patent applies local quality by differentiating motion vector precision requirements across different video regions. Through the offset vector mechanism, the system can apply higher precision motion vectors where needed (based on motion magnitude candidates) and lower precision where sufficient, optimizing the balance between prediction accuracy and data volume reduction on a local level.
Solution Approach 2:
The patent changes motion vector parameters through the offset vector derivation process. By adjusting the magnitude and direction of offset vectors based on motion magnitude and direction candidates, the system dynamically modifies motion vector precision parameters to achieve optimal compression performance while controlling data volume.
3Productivity
If compression algorithms are made more complex to improve compression rate, then video compression performance is improved, but device complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the motion vector refinement process into distinct stages: deriving the offset vector from motion magnitude candidates, determining the direction from direction candidates, and combining these to get the final motion vector. This segmented approach makes the complex compression algorithm more manageable and implementable while maintaining high compression performance.
Data Source
AI summary
A video decoding method according to the present disclosure includes the steps of: generating a merge candidate list for a current block; determining a merge candidate for the current block among merge candidates included in the merge candidate list; deriving an offset vector for the current block; and deriving a motion vector for the current block by adding the offset vector to a motion vector of the merge candidate.