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A DIRECT-type global optimization algorithm for image registration

Author

Listed:
  • Cuicui Zheng

    (New Jersey Institute of Technology)

  • James Calvin

    (New Jersey Institute of Technology)

  • Craig Gotsman

    (New Jersey Institute of Technology)

Abstract

Image registration is an important component of many image processing problems which often require optimizing over some set of parameters. In the image registration problem, one attempts to determine the best transformation for aligning similar images. Such problems typically require minimizing a dissimilarity measure with multiple local minima. We describe a global optimization algorithm and apply it to the problem of identifying the best transformation for aligning two images.

Suggested Citation

  • Cuicui Zheng & James Calvin & Craig Gotsman, 2021. "A DIRECT-type global optimization algorithm for image registration," Journal of Global Optimization, Springer, vol. 79(2), pages 431-445, February.
    • Handle: RePEc:spr:jglopt:v:79:y:2021:i:2:d:10.1007_s10898-020-00914-y
    DOI: 10.1007/s10898-020-00914-y
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    References listed on IDEAS

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    1. James Calvin & Gražina Gimbutienė & William O. Phillips & Antanas Žilinskas, 2018. "On convergence rate of a rectangular partition based global optimization algorithm," Journal of Global Optimization, Springer, vol. 71(1), pages 165-191, May.
    2. Giampaolo Liuzzi & Stefano Lucidi & Veronica Piccialli, 2010. "A partition-based global optimization algorithm," Journal of Global Optimization, Springer, vol. 48(1), pages 113-128, September.
    3. Albertas Gimbutas & Antanas Žilinskas, 2018. "An algorithm of simplicial Lipschitz optimization with the bi-criteria selection of simplices for the bi-section," Journal of Global Optimization, Springer, vol. 71(1), pages 115-127, May.
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