2006
DOI: 10.3390/s6121721
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Overview of Physical Models and Statistical Approaches for Weak Gaseous Plume Detection using Passive Infrared Hyperspectral Imagery

Abstract: 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 rese… Show more

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Cited by 37 publications
(57 citation statements)
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(108 reference statements)
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“…where A(ν) is the absorbance coefficient of the gas at wavenumber ν and has units of inverse ppm-m. For optically thin plumes [2], this term is well-approximated by a Taylor series expansion to the linear term, i.e.,…”
Section: Radiance Modelmentioning
confidence: 99%
See 3 more Smart Citations
“…where A(ν) is the absorbance coefficient of the gas at wavenumber ν and has units of inverse ppm-m. For optically thin plumes [2], this term is well-approximated by a Taylor series expansion to the linear term, i.e.,…”
Section: Radiance Modelmentioning
confidence: 99%
“…Hyperspectral images may contain on-plume pixels (pixels that have a gas plume that influences the signal) and off-plume pixels (pixels that do not have a gas plume influencing the signal) [2]. Using Equation (6) as a guide, the at-sensor observed radiance for an on-plume pixel, indexed i, can be modeled as:…”
Section: An Application To Hyperspectral Imagerymentioning
confidence: 99%
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“…His group performed many measurement campaigns with excellent results, mainly by ensuring proper modelling of the scene and by taking into account the signature of the instrument used. Other groups developed similar approaches, however limiting their study to optically thin plumes [3,4], to dedicated instruments performing optical subtraction [5,6], or introducing Bayesian algorithms to maximize the use of a priori information [7]. On the other hand, detection and quantification activities with an imaging Fourier-transform spectrometer (IFTS) have been first presented in [8].…”
Section: Introductionmentioning
confidence: 99%