Segmentation for hyperspectral images with priors

Authors:
Jian Ye;Todd Wittman;Xavier Bresson;Stanley Osher
Affiliations:
Department of Mathematics, University of California, Los Angeles, CA;Department of Mathematics, University of California, Los Angeles, CA;Department of Mathematics, University of California, Los Angeles, CA;Department of Mathematics, University of California, Los Angeles, CA
Venue:
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part II
Year:
2010

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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.