Multi-iteration Motion Vector Refinement for Video Coding
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Solution Overview
Problem
Current video coding technologies face challenges in refining motion information efficiently, particularly in deriving accurate motion vectors for effective video processing, which affects compression and decoding efficiency.
Innovation Solution
The implementation of a multi-step refinement processing method to iteratively derive refined motion vectors for video blocks, allowing for selective refinement based on video blocks and reference pictures, and performing video processing using these refined vectors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multi-step refinement processing is used to iteratively derive refined motion vectors, then motion information accuracy is improved, but processing complexity increases
Solution Approach 1:
The motion vector refinement process is divided into multiple iterative steps, where each step refines the motion vectors further. The motion information is segmented into initial motion vectors and refined motion vectors through successive refinement operations, allowing progressive improvement of accuracy while managing complexity through structured processing stages.
Solution Approach 2:
The refinement processing is performed selectively based on conditions such as video block characteristics and reference picture properties. The processing dynamically adapts by applying refinement only when beneficial, rather than uniformly to all blocks, thus improving motion accuracy where needed while reducing overall processing complexity through conditional execution.
2Measurement precision
If multi-step refinement processing is applied to all video blocks, then motion information accuracy is improved, but processing time increases
Solution Approach 1:
Instead of applying multi-step refinement processing to all video blocks uniformly, the method applies refinement selectively to specific video blocks based on their characteristics and reference picture conditions. This partial action approach ensures that refinement time is invested only where it provides the most benefit, reducing overall processing time while maintaining high accuracy for critical blocks.
Solution Approach 2:
The method performs preliminary assessment of video blocks to determine which ones require refinement processing. By evaluating block characteristics and reference picture properties beforehand, the system identifies candidate blocks for refinement, avoiding unnecessary processing of blocks that would not benefit from refinement, thus reducing total processing time.
Data Source
AI summary
A method for video processing includes: refining motion information of a video block by using a multi-step refinement processing, multiple refined motion vectors (MVs) of the video block being derived iteratively in respective steps of the multi-step refinement processing, and performing a video processing on the video block based on the multiple refined MVs of the video block.