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

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
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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 (CC BY 3.0).

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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.

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