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James Theiler, Clint Scovel, Brendt Wohlberg and Bernard R. Foy, "Elliptically Contoured Distributions for Anomalous Change Detection in Hyperspectral Imagery", IEEE Geoscience and Remote Sensing Letters, vol. 7, no. 2, doi:10.1109/LGRS.2009.2032565, pp. 271--275, Apr 2010

Abstract

We derive a class of algorithms for detecting anomalous changes in hyperspectral image pairs by modeling the data with elliptically contoured (EC) distributions. These algorithms are generalizations of well-known detectors that are obtained when the EC function is Gaussian. The performance of these EC-based anomalous change detectors is assessed on real data using both real and simulated changes. In these experiments, the EC-based detectors substantially outperform their Gaussian counterparts.

BibTeX Entry

@article{theiler-2010-elliptically,
author = {James Theiler and Clint Scovel and Brendt Wohlberg and Bernard R. Foy},
title = {Elliptically Contoured Distributions for Anomalous Change Detection in Hyperspectral Imagery},
year = {2010},
month = Apr,
urlpdf = {http://math.lanl.gov/~brendt/Publications/Docs/theiler-2010-elliptically.pdf},
journal = {IEEE Geoscience and Remote Sensing Letters},
volume = {7},
number = {2},
doi = {10.1109/LGRS.2009.2032565},
pages = {271--275}
}