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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

*  and
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 clutter; generalized least squares; infrared; model averaging; temperature-emissivity separation; errors in predictors; plume detection
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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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.

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