Motion Vector Predictor Selection for Video Coding Efficiency
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Solution Overview
Problem
The existing MPEG-4AVC/H.264 standard for moving picture compression coding often results in poor prediction precision and coding efficiency due to the limited ability to compress coding information effectively, leading to larger code sizes for motion vector differences.
Innovation Solution
A moving picture coding and decoding technology that derives multiple motion vector predictors and selects the optimal one to reduce code size, improving coding efficiency by calculating and selecting the best motion vector predictor candidates and coding information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If motion vector prediction is performed using a single prediction block, then device complexity is reduced, but prediction precision deteriorates
Solution Approach 1:
The current block is divided into multiple prediction blocks (first prediction block and second prediction block) to generate multiple motion vector predictors. This segmentation allows the system to evaluate multiple prediction candidates independently, improving prediction precision while keeping the complexity of each individual prediction simple.
Solution Approach 2:
The invention changes the parameter of prediction block quantity from single to multiple. By using multiple prediction blocks with different shapes and positions, the system generates diverse motion vector predictors, improving prediction accuracy without significantly increasing overall device complexity.
2Measurement precision
If multiple motion vector predictors are derived and selected, then prediction precision is improved, but device complexity increases
Solution Approach 1:
The system dynamically selects the optimal motion vector predictor from multiple candidates based on prediction performance. This dynamic selection process improves prediction precision while managing complexity by only performing detailed evaluations for the most promising candidates rather than all possible predictors.
Solution Approach 2:
The prediction system uses information from neighboring blocks and temporal references to automatically generate motion vector predictors without requiring complex external processing. This self-service approach improves precision through multiple candidates while keeping the generation process relatively simple.
3Device complexity
If motion vector difference coding is performed without optimization, then device complexity is reduced, but information loss increases
Solution Approach 1:
The system uses feedback from the selected motion vector predictor to optimize the coding of motion vector differences. By comparing the actual motion vector with the selected predictor and encoding only the difference, the system achieves better compression efficiency while maintaining manageable coding complexity through selective optimization.
Data Source
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AI summary
A motion vector predictor candidate generation unit 120 derives a plurality of motion vector predictor candidates by prediction from first coded prediction blocks neighboring a prediction block subject to coding within the same picture as the prediction block subject to coding, or from a second coded prediction block located at the same position as or in the neighborhood of the prediction block subject to coding in a picture different from that of the prediction block subject to coding, and adds the derived motion vector predictor candidates in a motion vector predictor candidate. The motion vector predictor candidate generation unit 120 determines, for the purpose of obtaining a predetermined number of motion vector predictor candidates, which of first coded prediction blocks provides the motion vector from which to derive the motion vector predictor candidate, organizing the blocks in the order of priority.