Motion-Compensated Frame Interpolation Based on Multihypothesis Motion Estimation and Texture Optimization

A novel motion-compensated frame interpolation (MCFI) algorithm to increase video temporal resolutions based on multihypothesis motion estimation and texture optimization is proposed in this paper. Initially, we form multiple motion hypotheses for each pixel by employing different motion estimation...

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Bibliographic Details
Published in:IEEE transactions on image processing 2013-11, Vol.22 (11), p.4497-4509
Main Authors: Jeong, Seong-Gyun, Lee, Chul, Kim, Chang-Su
Format: Article
Language:English
Subjects:
Algorithms
Applied sciences
Color
Data Compression - methods
Detection, estimation, filtering, equalization, prediction
Exact sciences and technology
exemplar-based texture synthesis
frame rate up-conversion
Heuristic algorithms
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods
Image processing
Information, signal and communications theory
Interpolation
Motion
Motion estimation
Motion segmentation
Motion-compensated frame interpolation
multihypothesis motion estimation
Optimization
Pattern recognition
Pattern Recognition, Automated - methods
Photography - methods
Reliability
Reproducibility of Results
Sensitivity and Specificity
Signal and communications theory
Signal processing
Signal, noise
Telecommunications and information theory
Video Recording - methods
video segmentation
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Summary:A novel motion-compensated frame interpolation (MCFI) algorithm to increase video temporal resolutions based on multihypothesis motion estimation and texture optimization is proposed in this paper. Initially, we form multiple motion hypotheses for each pixel by employing different motion estimation parameters, i.e., different block sizes and directions. Then, we determine the best motion hypothesis for each pixel by solving a labeling problem and optimizing the parameters. In the labeling problem, the cost function is composed of color, shape, and smoothness terms. Finally, we refine the motion hypothesis field based on the texture optimization technique and blend multiple source pixels to interpolate each pixel in the intermediate frame. Simulation results demonstrate that the proposed algorithm provides significantly better MCFI performance than conventional algorithms.
ISSN:1057-7149
1941-0042
DOI:10.1109/TIP.2013.2274731