Motion-Compensated frame interpolation based on multihypothesis motion estimation and texture optimization

Seong Gyun Jeong, Chul Lee, Chang-Su Kim

Research output: Contribution to journalArticle

36 Citations (Scopus)


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.

Original languageEnglish
Article number6567908
Pages (from-to)4497-4509
Number of pages13
JournalIEEE Transactions on Image Processing
Issue number11
Publication statusPublished - 2013 Sep 30



  • exemplar-based texture synthesis
  • frame rate up-conversion
  • Motion-compensated frame interpolation
  • multihypothesis motion estimation
  • video segmentation

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Software
  • Medicine(all)

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