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Proceedings Paper

Hyperspectral anomaly detection beyond RX
Author(s): A. P. Schaum
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Paper Abstract

The basic multivariate anomaly detector ("the RX algorithm") of Kelly and Reed remains little altered after nearly 30 years and performs reasonably well with hyperspectral imagery. However, better performance can be achieved in spectral applications by recognizing a deficiency in the hypothesis test that generates RX. The problem is commonly associated with the improved performance that results from deleting several high-variance clutter dimensions before applying RX, a procedure not envisioned in the original algorithm. There is, moreover, a better way to enhance detection than simply deleting the offending subspace. Instead of invoking the "additive target" model, one can exploit expected differences in spectral variability between target and background signals in the clutter dimensions. Several methods are discussed for achieving detection gain using this principle. Two of these are based on modifications to the RX hypothesis test. One results in Joint Subspace Detection, the other in an algorithm with a similar form but which does not postulate a clutter subspace. Each of these modifies the RX algorithm to incorporate clutter-dependent weights, including "anti-RX" terms in the clutter subspace. A newer approach is also described, which effects a nonlinear suppression of false alarms that are detected by an RX-type algorithm, employed as a preprocessor. Both techniques rely ultimately on the incorporation of simple spectral phenomenology into the detection process.

Paper Details

Date Published: 14 May 2007
PDF: 13 pages
Proc. SPIE 6565, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIII, 656502 (14 May 2007); doi: 10.1117/12.718789
Show Author Affiliations
A. P. Schaum, Naval Research Lab. (United States)


Published in SPIE Proceedings Vol. 6565:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIII
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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