
Proceedings Paper
Statistical models for LWIR hyperspectral backgrounds and their applications in chemical agent detectionFormat | Member Price | Non-Member Price |
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Paper Abstract
Remote detection of chemical vapors in the atmosphere has a wide range of civilian and military
applications. In the past few years there has been significant interest in the detection of effluent
plumes using hyperspectral imaging spectroscopy in the 8-13&mgr;m atmospheric window. A major obstacle
in the full exploitation of this technology is the fact that everything in the infrared is a source of
radiation. As a result, the emission from the gases of interest is always mixed with emission by the
more abundant atmospheric constituents and by other objects in the sensor field of view. The radiance
fluctuations in this background emission constitute an additional source of interference which is much
stronger than the detector noise. In this paper we develop and evaluate parametric models for the
statistical characterization of LWIR hyperspectral backgrounds. We consider models based on the
theory of elliptically contoured distributions. Both models can handle heavy tails, which is a key
stastical feature of hyperspectral imaging backgrounds. The paper provides a concise description of
the underlying models, the algorithms used to estimate their parameters from the background spectral
measurements, and the use of the developed models in the design and evaluation of chemical warfare
agent detection algorithms.
Paper Details
Date Published: 7 May 2007
PDF: 12 pages
Proc. SPIE 6565, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIII, 656525 (7 May 2007); doi: 10.1117/12.718378
Published in SPIE Proceedings Vol. 6565:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIII
Sylvia S. Shen; Paul E. Lewis, Editor(s)
PDF: 12 pages
Proc. SPIE 6565, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIII, 656525 (7 May 2007); doi: 10.1117/12.718378
Show Author Affiliations
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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