Motion Compensation Displacement Vector Selection Using Edge Feature Patterns
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Solution Overview
Problem
The displacement vector with the highest phase correlation degree in motion estimate and motion compensation (MEMC) algorithms does not necessarily reflect the actual motion of image blocks, leading to large deviations and poor moving image compensation effects.
Innovation Solution
A method and device that acquire and divide images into corresponding blocks, perform phase plane correlation to obtain displacement vectors with a phase correlation degree greater than a threshold, and use edge detection to determine a displacement vector matching the transformation between edge feature patterns, improving the accuracy of displacement vectors for motion compensation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If phase plane correlation method is used to determine displacement vector, then calculation speed is improved, but accuracy of displacement vector deviates from actual motion
Solution Approach 1:
The patent introduces edge feature patterns as an intermediary to bridge the phase plane correlation method and actual motion representation. By detecting edge features in image blocks and using them to select from multiple candidate displacement vectors, the system achieves both computational efficiency and accuracy. The edge features act as a mediator that guides the selection of the most representative displacement vector from the phase correlation results.
2Device complexity
If displacement vector with highest phase correlation degree is selected, then calculation is simplified, but representativeness of actual motion is worsened
Solution Approach 1:
Instead of relying on a single displacement vector from phase correlation, the patent calculates multiple candidate displacement vectors and then uses edge feature analysis to select the most appropriate one. This partial action approach - calculating a limited set of candidates rather than exhaustive options, then selecting based on edge features - balances computational complexity with motion representation accuracy.
Data Source
AI summary
Disclosed are a motion image compensation method and a device, and a display device. The motion image compensation method comprises: acquiring a first image corresponding to a pre-motion picture and a second image corresponding to a post-motion picture; dividing the first image and the second image respectively into several image blocks; performing computations on any pair of mutually corresponding image blocks in the first image and the second image based on a phase correlation method; performing edge detection on the first image and the second image respectively; and according to a preset condition, acquiring, from the at least one displacement vector, a displacement vector matched with a transformation between the edge feature patterns within the pair of mutually corresponding image blocks as a displacement vector corresponding to the pair of image blocks during a motion compensation process.