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Segmentation for Hyperspectral Images with Priors

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6454))

Abstract

In this paper, we extend the Chan-Vese model for image segmentation in [1] to hyperspectral image segmentation with shape and signal priors. The use of the Split Bregman algorithm makes our method very efficient compared to other existing segmentation methods incorporating priors. We demonstrate our results on aerial hyperspectral images.

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Ye, J., Wittman, T., Bresson, X., Osher, S. (2010). Segmentation for Hyperspectral Images with Priors. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2010. Lecture Notes in Computer Science, vol 6454. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17274-8_10

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  • DOI: https://doi.org/10.1007/978-3-642-17274-8_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17273-1

  • Online ISBN: 978-3-642-17274-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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