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Proceedings Paper

Active contours with edges: combining hyperspectral and grayscale segmentation
Author(s): Alex Chen
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Paper Abstract

In this work, we introduce a method to segment hyperspectral images using a Chan-Vese framework. We utilize a modified l2 distance especially well-suited for hyperspectral classification problems. This distance considers spectral signal shape rather than illumination for the classification of objects. The practicality of multiple phase segmentation in this application is also demonstrated. We then use a high spatial resolution grayscale or color image and a high spectral, but low spatial resolution hyperspectral image to produce a fused segmentation result that is more accurate than segmentation on either image alone. Lastly, we show that the algorithm also gives a natural method for end member selection and apply this result to anomaly detection.

Paper Details

Date Published: 8 November 2012
PDF: 9 pages
Proc. SPIE 8537, Image and Signal Processing for Remote Sensing XVIII, 85370B (8 November 2012); doi: 10.1117/12.974445
Show Author Affiliations
Alex Chen, The Univ. of North Carolina at Chapel Hill (United States)

Published in SPIE Proceedings Vol. 8537:
Image and Signal Processing for Remote Sensing XVIII
Lorenzo Bruzzone, Editor(s)

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