Maximum a posteriori video super-resolution using a new multichannel image prior

  • Authors:

  • Stefanos P. Belekos;Nikolaos P. Galatsanos;Aggelos K. Katsaggelos

  • Affiliations:

  • Faculty of Physics, Department of Electronics, Computers, Telecommunications and Control, National and Kapodistrian University of Athens, Athens, Greece;Department of Electrical and Computer Engineering, University of Patras, Rio, Greece;Department of Electrical Engineering and Computer Science, Northwestern University, Evanston, IL and Faculty of Physics, National and Kapodistrian University of Athens, Greece

  • Venue:
  • IEEE Transactions on Image Processing
  • Year:
  • 2010

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Abstract

Super-resolution (SR) is the term used to define the process of estimating a high-resolution (HR) image or a set of HR images from a set of low-resolution (LR) observations. In this paper we propose a class of SR algorithms based on the maximum a posteriori (MAP) framework. These algorithms utilize a new multichannel image prior model, along with the state-of-the-art single channel image prior and observation models. A hierarchical (twolevel) Gaussian nonstationary version of the multichannel prior is also defined and utilized within the same framework. Numerical experiments comparing the proposed algorithms among themselves and with other algorithms in the literature, demonstrate the advantages of the adopted multichannel approach.