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Sensors 2006, 6(11), 1587-1615; doi:10.3390/s6111587
Article

Characterizing Clutter in the Context of Detecting Weak Gaseous Plumes in Hyperspectral Imagery

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Received: 29 September 2006; Accepted: 17 November 2006 / Published: 23 November 2006
(This article belongs to the Special Issue Gas Sensors)
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Abstract: Weak gaseous plume detection in hyperspectral imagery requires thatbackground clutter consisting of a mixture of components such as water, grass, and asphaltbe well characterized. The appropriate characterization depends on analysis goals.Although we almost never see clutter as a single-component multivariate Gaussian(SCMG), alternatives such as various mixture distributions that have been proposed mightnot be necessary for modeling clutter in the context of plume detection when the chemicaltargets that could be present are known at least approximately. Our goal is to show to whatextent the generalized least squares (GLS) approach applied to real data to look for evidenceof known chemical targets leads to chemical concentration estimates and to chemicalprobability estimates (arising from repeated application of the GLS approach) that aresimilar to corresponding estimates arising from simulated SCMG data. In some cases,approximations to decision thresholds or confidence estimates based on assuming the clutterhas a SCMG distribution will not be sufficiently accurate. Therefore, we also describe astrategy that uses a scene-specific reference distribution to estimate decision thresholds forplume detection and associated confidence measures.
Keywords: clutter; single-component multivariate Gaussian; mixture distribution; generalized least squares; near infrared; central limit theorem clutter; single-component multivariate Gaussian; mixture distribution; generalized least squares; near infrared; central limit theorem
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Burr, T.; Foy, B.; Fry, H.; McVey, B. Characterizing Clutter in the Context of Detecting Weak Gaseous Plumes in Hyperspectral Imagery. Sensors 2006, 6, 1587-1615.

AMA Style

Burr T, Foy B, Fry H, McVey B. Characterizing Clutter in the Context of Detecting Weak Gaseous Plumes in Hyperspectral Imagery. Sensors. 2006; 6(11):1587-1615.

Chicago/Turabian Style

Burr, Tom; Foy, Bernie; Fry, Herb; McVey, Brian. 2006. "Characterizing Clutter in the Context of Detecting Weak Gaseous Plumes in Hyperspectral Imagery." Sensors 6, no. 11: 1587-1615.



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