Vector Difference Candidate Lists With Multi-Pel Interval Selection
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Solution Overview
Problem
Existing video coding techniques face inefficiencies due to increased computational complexity and delays when constructing vector difference candidate lists with higher granularity and directions, leading to excessive calculations.
Innovation Solution
The techniques dynamically determine vector difference candidates based on varying pel-intervals to construct a vector difference candidate list, ensuring more desirable candidates are included while minimizing processing time inefficiencies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the granularity of distance between vector difference candidates and the number of directions are increased, then coding gain is improved, but the number of calculations for template matching increases
Solution Approach 1:
The patent segments the vector difference candidate selection process into multiple stages: first constructing a reduced candidate list with a subset of candidates, then performing template matching only on this reduced set. This segmentation reduces the total number of calculations while maintaining the ability to evaluate multiple directions and granularities when needed.
Solution Approach 2:
The patent dynamically determines which vector difference candidates to evaluate based on reduced template matching calculations. The system adaptively selects candidates from the constructed list, evaluating only those most likely to provide coding gain, rather than uniformly evaluating all candidates across all directions and granularities.
2Measurement precision
If the number of vector difference candidates is increased, then coding gain is improved, but coding delay increases due to increased calculations
Solution Approach 1:
The patent divides the candidate evaluation process into two phases: first constructing a comprehensive candidate list with multiple candidates at various granularities and directions, then performing template matching only on a reduced subset of this list. This reduces coding delay while preserving the option to consider many candidates.
Solution Approach 2:
The patent performs preliminary construction of the vector difference candidate list before template matching. By pre-organizing candidates based on pel-intervals and directions, the system prepares the candidate set in advance, reducing the computational burden during the time-critical template matching phase.
3Measurement precision
If template matching is performed on all vector difference candidates, then accurate candidate selection is achieved, but processing time increases
Solution Approach 1:
The patent extracts only the most promising vector difference candidates from the full candidate list for template matching evaluation. By identifying and extracting a reduced subset of candidates based on preliminary criteria (pel-intervals, directions), the system performs template matching on fewer items while maintaining selection accuracy.
Solution Approach 2:
The patent performs template matching on a partial set of candidates rather than all candidates. The reduced candidate list contains enough candidates to achieve accurate selection (partial action) without the computational cost of evaluating every possible candidate, optimizing the trade-off between accuracy and processing speed.
Data Source
AI summary
A method of decoding video data includes determining a vector predictor for a current block; determining a first set of vector difference candidates based on a first pel-interval, the first pel-interval defining a first distance between consecutive vector difference candidates in the first set of vector difference candidates starting with the vector predictor; determining a second set of vector difference candidates based on the first set of vector difference candidates and a second pel-interval, the second pel-interval defining a second distance between consecutive vector difference candidates in the second set of vector difference candidates; constructing a vector difference candidate list based on the second set of vector difference candidates; determining a vector for the current block based on the vector predictor and a vector difference from the vector difference candidate list; and reconstructing the current block based on the vector for the current block.