EM-Based Simultaneous Registration, Restoration, and Interpolation of Super-resolved Images

Nathan A. Woods*, Nikolas P. Galatsanos, Aggelos K Katsaggelos

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

20 Scopus citations

Abstract

We present a maximum likelihood (ML) solution to the problem of obtaining high-resolution images from sequences of noisy, blurred, and low-resolution images. In our formulation, the registration parameters of the low-resolution images, the degrading blur, and noise variance are unknown. Our algorithm has the advantage that all unknown parameters are obtained simultaneously using all of the available data. An efficient implementation is presented in the frequency domain, based on the Expectation Maximization (EM) algorithm. Simulations demonstrate the effectiveness of the algorithm.

Original languageEnglish (US)
Title of host publicationIEEE International Conference on Image Processing
Pages303-306
Number of pages4
Volume2
StatePublished - Dec 17 2003
EventProceedings: 2003 International Conference on Image Processing, ICIP-2003 - Barcelona, Spain
Duration: Sep 14 2003Sep 17 2003

Other

OtherProceedings: 2003 International Conference on Image Processing, ICIP-2003
CountrySpain
CityBarcelona
Period9/14/039/17/03

ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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