Sensors 2006, 6(12), 1721-1750; doi:10.3390/s6121721
Review

Overview of Physical Models and Statistical Approaches for Weak Gaseous Plume Detection using Passive Infrared Hyperspectral Imagery

Mail Stop F600, Los Alamos National Laboratory, Los Alamos NM 87545, USA
* Author to whom correspondence should be addressed.
Received: 22 October 2006; Accepted: 4 December 2006 / Published: 6 December 2006
(This article belongs to the Special Issue Gas Sensors)
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Abstract: The performance of weak gaseous plume-detection methods in hyperspectral long-wave infrared imagery depends on scene-specific conditions such at the ability to properly estimate atmospheric transmission, the accuracy of estimated chemical signatures, and background clutter. This paper reviews commonly-applied physical models in the context of weak plume identification and quantification, identifies inherent error sources as well as those introduced by making simplifying assumptions, and indicates research areas.
Keywords: clutter; generalized least squares; infrared; model averaging; temperature-emissivity separation; errors in predictors; plume detection

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MDPI and ACS Style

Burr, T.; Hengartner, N. Overview of Physical Models and Statistical Approaches for Weak Gaseous Plume Detection using Passive Infrared Hyperspectral Imagery. Sensors 2006, 6, 1721-1750.

AMA Style

Burr T, Hengartner N. Overview of Physical Models and Statistical Approaches for Weak Gaseous Plume Detection using Passive Infrared Hyperspectral Imagery. Sensors. 2006; 6(12):1721-1750.

Chicago/Turabian Style

Burr, Tom; Hengartner, Nicolas. 2006. "Overview of Physical Models and Statistical Approaches for Weak Gaseous Plume Detection using Passive Infrared Hyperspectral Imagery." Sensors 6, no. 12: 1721-1750.

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