Gas detection from smoke stacks: Finding multiple constituent gases in a plume using infrared hyperspectral data

D. N. Rotman, S. R. Rotman, D. G. Blumberg, E. Ontiveros, D. Messinger

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

An iterative algorithm which identifies the presence of different gases using a hyperspectral image was developed and tested. The algorithm uses the "stepwise regression" method combined with new methods of detection and identification. This algorithm begins with a library of gas signatures; an initial fit is done with all the gases. The algorithm then eliminates those signatures which do not noticeably improve the fit to the measured signature. We then consider which of the gases that were detected have a high probability of being mistaken with the detection of other gases that are also present in the scene. A necessary post-processing step eliminates gases which do not uniquely fit the signature of the examined pixel, with an emphasis on eliminating gases which may have been misidentified.

Original languageEnglish
Title of host publicationElectro-Optical Remote Sensing, Photonic Technologies, and Applications V
DOIs
StatePublished - 18 Nov 2011
EventElectro-Optical Remote Sensing, Photonic Technologies, and Applications V - Prague, Czech Republic
Duration: 19 Sep 201122 Sep 2011

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume8186
ISSN (Print)0277-786X

Conference

ConferenceElectro-Optical Remote Sensing, Photonic Technologies, and Applications V
Country/TerritoryCzech Republic
CityPrague
Period19/09/1122/09/11

Keywords

  • Gas detection
  • Longwave infrared
  • Stepwise regression

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