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Proceedings Paper

A new approach to anomaly detection in hyperspectral images
Author(s): Philip E. Clare; Mark Bernhardt; William J. Oxford; Sean Murphy; Peter Godfree; Vicky Wilkinson
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Paper Abstract

Anomaly detection in hyperspectral imagery is a potentially powerful approach for detecting objects of military interest because it does not require atmospheric compensation or target signature libraries. A number of methods have been proposed in the literature, most of these require a parametric model of the background probability distribution to be estimated from the data. There are two potential difficulties with this. First a parametric model must be postulated which is capable of describing the background statistics to an adequate approximation. Most work has made use of the multivariate normal distribution. Secondly the parameters must be estimated sufficiently accurately - this can be problematic for the covariance matrix of high dimensional hyperspectral data. In this paper we present an alternative view and investigate the capabilities of anomaly detection algorithms starting from a minimal set of assumptions. In particular we only require the background pixels to be samples from an independent and identically distributed (iid) process, but do not require the construction of a model for this distribution. We investigate a number of simple measures of the 'strangeness' of a given pixel spectra with respect to the observed background. An algorithm is proposed for detecting anomalies in a self-consistent way. The effectiveness of the algorithms is compared with a well-known anomaly detection algorithm from the literature on real hyperspectral data sets.

Paper Details

Date Published: 23 September 2003
PDF: 12 pages
Proc. SPIE 5093, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery IX, (23 September 2003); doi: 10.1117/12.487030
Show Author Affiliations
Philip E. Clare, Defence Science and Technology Lab. (United Kingdom)
Mark Bernhardt, Quantinuity Ltd. (United Kingdom)
William J. Oxford, Defence Science and Technology Lab. (United Kingdom)
Sean Murphy, Defence Science and Technology Lab. (United Kingdom)
Peter Godfree, Defence Science and Technology Lab. (United Kingdom)
Vicky Wilkinson, Defence Science and Technology Lab. (United Kingdom)


Published in SPIE Proceedings Vol. 5093:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery IX
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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