Bi-Predictive Motion Vector Selection via Candidate Extraction
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Solution Overview
Problem
Current video encoding and decoding methods face challenges in efficiently handling bi-predictive blocks, particularly in selecting optimal reference pictures for motion vector determination, which affects compression efficiency and processing complexity.
Innovation Solution
A method and apparatus for video encoding and decoding that determine and select motion vector candidates from two reference picture lists for bi-predictive blocks, including one candidate in the list of motion vector candidates while excluding the other, based on criteria such as matching cost ratios and template areas, to refine motion vectors using template or bilateral modes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If both first candidate and second candidate are included in the motion vector candidate list for bi-predictive blocks, then motion vector accuracy is improved, but processing complexity increases
Solution Approach 1:
The patent extracts only one candidate from the bi-predictive block candidates into the motion vector candidate list, rather than including both. This selective extraction reduces the number of candidates processed while maintaining sufficient motion vector accuracy for compression efficiency.
2Adaptability or versatility
If both first candidate and second candidate are included in the motion vector candidate list, then motion vector selection options are improved, but encoding/decoding time increases
Solution Approach 1:
The patent extracts a single representative candidate from the bi-predictive block candidates and includes only that one in the motion vector candidate list. This reduces the time required for encoding and decoding while preserving adequate motion vector selection flexibility.
3Measurement precision
If both first candidate and second candidate are included in the motion vector candidate list, then prediction accuracy is improved, but compression efficiency deteriorates
Solution Approach 1:
The patent extracts one candidate from the bi-predictive block candidates and includes it in the motion vector candidate list. This selective approach maintains sufficient prediction accuracy while improving compression efficiency by reducing the information that needs to be encoded and transmitted.
Data Source
AI summary
A Frame Rate Up-Conversion (FRUC) derivation process, based on frame rate up-conversion techniques, is developed in the reference software JEM (Joint Exploration Model) by the Joint Video Exploration Team (JVET). In one embodiment, a modified FRUC derivation process improves the performances of the current FRUC tool is provided. For example, some candidates of a bi-predictive pair may be discarded initially, which would save signification processing time. The discarding decision may depend on various criteria such as, e.g., a ratio between matching costs of a bi-predictive pair from two reference picture lists, a difference between the matching costs of a bi-predictive pair normalized by their respective template areas.