Video Coding Block Vector Predictor Refinement
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Solution Overview
Problem
Current video coding technologies face inefficiencies in intra picture block compensation, particularly in refining block vector predictors to minimize cost function values, which affects coding efficiency and compression ratios.
Innovation Solution
The processing circuitry calculates cost function values for block vector predictors and determines a refined predictor with the smallest value, using a candidate list and template match costs to reconstruct samples, thereby improving prediction accuracy and reducing redundancy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If traditional intra coding without intra prediction is used, then device complexity is reduced, but compression efficiency deteriorates
Solution Approach 1:
The patent performs preliminary actions by constructing a candidate list of block vector predictors and calculating cost function values for each candidate before final selection. This preliminary processing enables the system to efficiently identify the optimal predictor without exhaustive search, resolving the contradiction between complexity and compression efficiency.
Solution Approach 2:
The patent segments the prediction process into distinct stages: candidate generation, cost function evaluation, and refined predictor selection. By dividing the overall prediction task into manageable segments with specific functions, the system achieves high compression efficiency while maintaining controlled device complexity.
2Measurement precision
If block vector predictor refinement with cost function calculation is performed, then prediction accuracy is improved, but processing time increases
Solution Approach 1:
The patent applies partial action by calculating cost function values for a limited set of candidate predictors rather than all possible predictors. This selective approach achieves sufficient prediction accuracy while significantly reducing processing time compared to exhaustive evaluation.
Solution Approach 2:
The patent changes parameters by using a cost function that combines template match cost and gradient cost, allowing the system to evaluate predictor quality efficiently. This parameter-based evaluation method achieves high prediction accuracy without requiring excessive processing time.
3Device complexity
If a limited candidate list for block vector predictors is used, then processing complexity is reduced, but prediction accuracy may deteriorate
Solution Approach 1:
The patent implements feedback by using gradient information to refine the block vector predictor selection. The gradient cost component provides feedback on the quality of candidate predictors, enabling the system to maintain high prediction accuracy even with a limited candidate list by prioritizing the most promising candidates.
Data Source
AI summary
Aspects of the disclosure provide method and apparatus for video coding. In some examples, an apparatus includes processing circuitry for video decoding. The processing circuitry calculates cost function values for refined block vector positions. The refined bock vector positions are determined based on a position of a block vector predictor for a block vector of a current block in a picture. The processing circuitry determines a refined block vector predictor for the block vector of the current block based on the refined block vector position that has a smallest cost function value among the cost function values. Further, the processing circuitry reconstructs at least one sample of the current block based on the refined block vector predictor.