Motion Vector Estimation Using Confidence Degree for Video Jitter Reduction
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Solution Overview
Problem
Existing methods for increasing video frame rate, such as motion estimation and motion compensation, often result in video jitters and unsmoothness due to unreliable motion vector estimation, especially when multiple candidate motion vectors have similar minimum block matching errors.
Innovation Solution
A method that uses a down-sampled candidate motion vector as a reference to calculate a confidence degree for other candidate motion vectors, determining the most reliable motion vector by assessing their difference values, thereby improving estimation accuracy and reducing video jitters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple candidate motion vectors are generated with minimum block matching error, then the motion estimation covers more possibilities, but the reliability of motion vector selection decreases when multiple candidates have similar errors
Solution Approach 1:
The patent changes the parameter used for motion vector selection from block matching error alone to a confidence degree metric. This confidence degree is calculated based on the difference between candidate motion vectors and a reference motion vector, providing a new criterion that resolves ties when multiple candidates have similar matching errors.
Solution Approach 2:
The patent introduces a reference motion vector as an intermediary element. This reference vector serves as a benchmark against which all candidate motion vectors are compared to calculate confidence degrees, mediating the selection process between multiple equally viable candidates.
2Device complexity
If hierarchical search strategy is applied to reduce computational complexity, then the search resolution is reduced at higher levels, but the motion vector estimation accuracy may be compromised
Solution Approach 1:
The patent performs preliminary action by generating a reference motion vector early in the process using hierarchical search. This reference vector is then used to evaluate all candidate motion vectors, allowing the system to benefit from both the computational efficiency of hierarchical search and the accuracy of fine-grained evaluation.
Solution Approach 2:
The patent adds another dimension to the motion vector evaluation by introducing confidence degree calculation based on difference values. This transforms the selection criterion from a single-dimensional block matching error to a multi-dimensional assessment including confidence relative to a reference vector.
Data Source
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AI summary
The present disclosure discloses a method for estimating a motion vector of a pixel block, a video processing apparatus, an electronic device and a storage medium. The method for estimating the motion vector of the pixel block includes:obtaining a plurality of candidate motion vectors of a current pixel block in a current video frame, the plurality of candidate motion vectors comprising at least a down-sampled candidate motion vector; calculating a confidence degree for a difference value between each of other candidate motion vectors except for the down-sampled candidate motion vector in the plurality of candidate motion vectors and the down-sampled candidate motion vector; and determining one candidate motion vector in the other candidate motion vectors as the motion vector of the current pixel block, the confidence degree for the difference value between the one candidate motion vector and the down-sampled candidate motion vector is highest. The method, video processing apparatus and electronic device of the present disclosure may obtain a more correct motion vector from candidate motion vectors, improve reliability of motion estimation, reduce video jitters or unsmoothness, and improve a video playing effect.