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A review of level set and fast marching methods for image processing

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Modern Methods in Scientific Computing and Applications

Part of the book series: NATO Science Series ((NAII,volume 75))

Abstract

In recent years, a considerable amount of work has been developed concerning a partial differential equations-based approach to image processing. This work has been focussed on the interplay between geometric motion and non-linear evolution equations, and its applicability to problems in image enhancement and denoising, image segmentation, and shape recognition and classification. In this review article, we provide an overview for some of these ideas.

This work was supported in part by the Applied Mathematical Science subprogram of the Office of Energy Research, U.S. Department of Energy, under Contract Number DE-AC03-76SF00098, and the Division of Mathematical Sciences of the National Science Foundation.

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Author information

Authors and Affiliations

  1. Department of Mathematics, University of California, Berkeley, CA, 94720, USA

    J. A. Sethian

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  1. J. A. Sethian
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Editors and Affiliations

  1. Département de Mathématiques et de Statistique, Université de Montréal, Montréal, Québec, Canada

    Anne Bourlioux  & Gert Sabidussi  & 

  2. Department of Mathematics and Statistics, McGill University, Montréal, Québec, Canada

    Martin J. Gander

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© 2002 Springer Science+Business Media Dordrecht

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Sethian, J.A. (2002). A review of level set and fast marching methods for image processing. In: Bourlioux, A., Gander, M.J., Sabidussi, G. (eds) Modern Methods in Scientific Computing and Applications. NATO Science Series, vol 75. Springer, Dordrecht. https://doi.org/10.1007/978-94-010-0510-4_10

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  • DOI: https://doi.org/10.1007/978-94-010-0510-4_10

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-1-4020-0782-8

  • Online ISBN: 978-94-010-0510-4

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