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International Parallel Processing Symposium

IPPS 1999: Parallel and Distributed Processing pp 257–265Cite as

GA-based parallel image registration on parallel clusters

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1586))

Abstract

Genetic Algorithms (GAs) have been known to be robust for search and optimization problems. Image registration can take advantage of the robustness of GAs in finding best transformation between two images, of the same location with slightly different orientation, produced by moving spaceborne remote sensing instruments. In this paper, we have developed sequential and coarse-grained parallel image registration algorithms using GA as an optimization mechanism. In its first phase the algorithm finds a small set of good solutions using low-resolution versions of the images. Based on the results from the first phase, the algorithm uses full resolution image data to refine the final registration results in the second phase. Experimental results are presented and we found that our algorithms yield very accurate registration results and the parallel algorithms scales quite well on the Beowulf parallel cluster.

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Author information

Authors and Affiliations

  1. Institute for Computational Sciences and Informatics, George Mason University, USA

    Prachya Chalermwat & Tarek El-Ghazawi

  2. NASA Goddard Space Flight Center, 2 Code 935, USA

    Jacqueline LeMoigne

Authors
  1. Prachya Chalermwat
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  2. Tarek El-Ghazawi
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  3. Jacqueline LeMoigne
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Editor information

José Rolim Frank Mueller Albert Y. Zomaya Fikret Ercal Stephan Olariu Binoy Ravindran Jan Gustafsson Hiroaki Takada Ron Olsson Laxmikant V. Kale Pete Beckman Matthew Haines Hossam ElGindy Denis Caromel Serge Chaumette Geoffrey Fox Yi Pan Keqin Li Tao Yang G. Chiola G. Conte L. V. Mancini Domenique Méry Beverly Sanders Devesh Bhatt Viktor Prasanna

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© 1999 Springer-Verlag

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Chalermwat, P., El-Ghazawi, T., LeMoigne, J. (1999). GA-based parallel image registration on parallel clusters. In: Rolim, J., et al. Parallel and Distributed Processing. IPPS 1999. Lecture Notes in Computer Science, vol 1586. Springer, Berlin, Heidelberg . https://doi.org/10.1007/BFb0097907

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  • DOI: https://doi.org/10.1007/BFb0097907

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-65831-3

  • Online ISBN: 978-3-540-48932-0

  • eBook Packages: Springer Book Archive

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