Fast image registration with non-stationary Gauss-Markov random field templates

Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Andreas Spanias

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

4 Scopus citations

Abstract

Non-stationary Gauss-Markov random fields are required in modeling images with complex patterns. In this paper, we propose a framework for registering images to a nonstationary Gauss-Markov random field template in anM x M lattice, with a complexity of order M2 logM, considering only global translations. We simplify the likelihood computation by expressing it as a scalar product and we estimate the maximal likelihood translation using 2-D FFTs. We demonstrate the utility of this framework by applying it to image registration in a wavelet-domain template learning application. Results reveal that significant complexity reduction is achieved in image registration compared to straightforward registration in the wavelet domain.

Original languageEnglish (US)
Title of host publication2009 IEEE International Conference on Image Processing, ICIP 2009 - Proceedings
PublisherIEEE Computer Society
Pages185-188
Number of pages4
ISBN (Print)9781424456543
DOIs
StatePublished - Jan 1 2009
Event2009 IEEE International Conference on Image Processing, ICIP 2009 - Cairo, Egypt
Duration: Nov 7 2009Nov 10 2009

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Other

Other2009 IEEE International Conference on Image Processing, ICIP 2009
CountryEgypt
CityCairo
Period11/7/0911/10/09

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Keywords

  • Discrete Fourier transforms
  • Gauss-Markov random field
  • Image registration
  • Pattern matching

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

Cite this

Ramamurthy, K. N., Thiagarajan, J. J., & Spanias, A. (2009). Fast image registration with non-stationary Gauss-Markov random field templates. In 2009 IEEE International Conference on Image Processing, ICIP 2009 - Proceedings (pp. 185-188). [5414177] (Proceedings - International Conference on Image Processing, ICIP). IEEE Computer Society. https://doi.org/10.1109/ICIP.2009.5414177