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

Stefanos P. Belekos, Nikolaos P. Galatsanos, Aggelos K. Katsaggelos

Research output: Contribution to journalArticlepeer-review

128 Scopus citations


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 (two-level) 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.

Original languageEnglish (US)
Article number5404316
Pages (from-to)1451-1464
Number of pages14
JournalIEEE Transactions on Image Processing
Issue number6
StatePublished - Jun 2010


  • Image restoration
  • Maximum a posteriori (MAP) framework
  • Motion field estimation
  • Multichannel prior
  • Observation model
  • Parameter estimation
  • Super-resolution
  • Video applications

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design


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