EC-GLRT: Detecting Weak Plumes in Non-Gaussian Hyperspectral Clutter Using an Elliptically-Contoured Generalized Likelihood Ratio Test

Author

Theiler, James ; Foy, Bernard R.

Author_Institution

Los Alamos Nat. Lab., Los Alamos, NM

Volume

1

fYear

2008

fDate

7-11 July 2008

Abstract

We investigate the behavior of a detector for weak gaseous plumes in hyperspectral imagery that can be derived in terms of a generalized likelihood ratio test (GLRT) applied to an elliptically-contoured (EC) model for the distribution of background clutter. Two limiting cases of this EC-GLRT detector are the adaptive matched filter (AMF) and the adaptive coherence estimator (ACE). While the general EC-GLRT detector does not share the specific optimality or invariance properties exhibited by these limiting cases, it provides an in-between model that can be competitive with both of them over a broad range of scenarios.

Keywords

adaptive filters; atmospheric composition; clutter; matched filters; remote sensing; ACE; AMF; EC-GLRT detector; adaptive coherence estimator; adaptive matched filter; background clutter distribution; elliptically-contoured model; gaseous plumes; generalized likelihood ratio test; hyperspectral imagery; invariance properties; nonGaussian hyperspectral clutter; Chemical products; Coherence; Detectors; Hyperspectral imaging; Laboratories; Light rail systems; Matched filters; Maximum likelihood detection; Statistical distributions; Testing; chemical plume; generalized likelihood ratio test; hyperspectral imagery; matched filter; non-Gaussian distribution;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008. IEEE International

Conference_Location

Boston, MA

Print_ISBN

978-1-4244-2807-6

Electronic_ISBN

978-1-4244-2808-3

Type

conf

DOI

10.1109/IGARSS.2008.4778833

Filename

4778833