Bayesian high resolution image reconstruction with incomplete multisensor low resolution systems

Javier Mateos*, Rafael Molina, Aggelos K Katsaggelos

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

In this paper we consider the problem of reconstructing a high-resolution image from an incomplete set of undersampled, shifted, degraded frames with subpixel displacement errors. We derive mathematical expressions for the calculation of the maximum a posteriori (MAP) estimate of the high resolution image given the low resolution observed images. We also examine the role played by the prior model when an incomplete set of low resolution images is used. Finally, the proposed method is tested on real and synthetic images.

Original languageEnglish (US)
Pages (from-to)705-708
Number of pages4
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume3
StatePublished - Sep 25 2003

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Signal Processing
  • Acoustics and Ultrasonics

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