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Multiframe Motion Coupling for Video Super Resolution

  • Jonas GeipingEmail author
  • Hendrik Dirks
  • Daniel Cremers
  • Michael Moeller
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10746)

Abstract

The idea of video super resolution is to use different view points of a single scene to enhance the overall resolution and quality. Classical energy minimization approaches first establish a correspondence of the current frame to all its neighbors in some radius and then use this temporal information for enhancement. In this paper, we propose the first variational super resolution approach that computes several super resolved frames in one batch optimization procedure by incorporating motion information between the high-resolution image frames themselves. As a consequence, the number of motion estimation problems grows linearly in the number of frames, opposed to a quadratic growth of classical methods and temporal consistency is enforced naturally.

We use infimal convolution regularization as well as an automatic parameter balancing scheme to automatically determine the reliability of the motion information and reweight the regularization locally. We demonstrate that our approach yields state-of-the-art results and even is competitive with machine learning approaches.

Notes

Acknowledgements

J.G. and M.M. acknowledge the support of the German Research Foundation (DFG) via the research training group GRK 1564 Imaging New Modalities. D.C. was partially funded by the ERC Consolidator grant 3D Reloaded.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Jonas Geiping
    • 1
    Email author
  • Hendrik Dirks
    • 2
  • Daniel Cremers
    • 3
  • Michael Moeller
    • 1
  1. 1.University of SiegenSiegenGermany
  2. 2.University of MünsterMünsterGermany
  3. 3.Technical University of MunichMunichGermany

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