A Convex Approach for Variational Super-Resolution

  • Markus Unger
  • Thomas Pock
  • Manuel Werlberger
  • Horst Bischof
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6376)


We propose a convex variational framework to compute high resolution images from a low resolution video. The image formation process is analyzed to provide to a well designed model for warping, blurring, downsampling and regularization. We provide a comprehensive investigation of the single model components. The super-resolution problem is modeled as a minimization problem in an unified convex framework, which is solved by a fast primal dual algorithm. A comprehensive evaluation on the influence of different kinds of noise is carried out. The proposed algorithm shows excellent recovery of information for various real and synthetic datasets.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Markus Unger
    • 1
  • Thomas Pock
    • 1
  • Manuel Werlberger
    • 1
  • Horst Bischof
    • 1
  1. 1.Institute for Computer Graphics and VisionGraz University of TechnologyAustria

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