Video Signal Motion Vector Scaling for Temporal Prediction Accuracy
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Solution Overview
Problem
Existing video compression methods face inaccuracies in motion vector prediction due to the use of neighboring partition motion vectors without considering temporal distance differences between reference pictures, limited candidate groups, and increased complexity in selection processes.
Innovation Solution
The method involves scaling neighboring motion vectors based on temporal distance differences between reference pictures, extending candidate groups, and applying unified priority search conditions to improve motion vector prediction accuracy and reduce complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If neighboring partition motion vectors are used for prediction without considering temporal distance differences, then the prediction process is simple, but the prediction accuracy decreases
Solution Approach 1:
The patent applies motion vector scaling by changing the temporal distance parameter. When the reference picture of a neighboring partition differs from the current partition's reference picture, the motion vector is scaled according to the ratio of temporal distances: MV_scaled = MV_original × (temporal_distance_current / temporal_distance_neighboring). This parameter adjustment resolves the contradiction by improving prediction accuracy through temporal distance consideration while maintaining a relatively simple scaling calculation process.
2Reliability
If neighboring motion vector candidate group is limited to partitions with the same reference picture list and reference picture, then the selection process is simple, but the probability of acquiring an available neighboring motion vector decreases
Solution Approach 1:
The patent dynamically extends the candidate group selection criteria. Instead of rigidly limiting candidates to partitions with identical reference picture lists and reference pictures, the method dynamically includes neighboring partitions that may have different reference picture lists or reference pictures, provided they are spatially adjacent. This dynamic expansion increases the probability of finding available motion vectors while managing complexity through structured selection rules.
3Measurement precision
If the number of neighboring motion vector candidates is increased, then the prediction accuracy may improve, but the complexity of the selection process increases
Solution Approach 1:
The patent segments the candidate selection process into distinct stages: first identifying spatially adjacent neighboring partitions, then filtering based on reference picture list and reference picture criteria, and finally applying motion vector scaling where needed. This segmentation of the selection process allows for a larger number of candidates to be considered systematically while managing complexity through organized, step-by-step evaluation criteria.
Data Source
AI summary
The present invention relates to a method and apparatus for processing a video signal, which can increase the accuracy of the motion vector prediction through motion vector scaling which takes a difference in the temporal distance between reference pictures into consideration. To this end, the present invention provides a video signal processing method and a video signal processing apparatus using the same, and the method comprises the steps of: scaling at least one neighboring partition motion vector for a motion vector prediction of the current partition; scaling the neighboring partition motion vector, which has been selected, when the reference picture of the neighboring partition motion vector is different from the reference picture of the current partition; acquiring a motion vector prediction value of the current partition using the scaled motion vector; and acquiring a motion vector of the current partition using the motion vector prediction value.