Anomaly gas remote sensing and tracking using a field-portable imaging thermal radiometric spectrometer

Eran Ohel, Stanley Rotman, Dan Blumberg, Lior Sagiv

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

1 Scopus citations

Abstract

Using a set of radiometric thermal hyperspectral data cubes, we developed an algorithm which detects the formation of an anomalous gas cloud. Once we've established the presence of the cloud in the latter images, we determine the origin of the cloud in the earlier ones and track its propagation. Gas usually expands from point sources and it is difficult to know whether it is significant when it occupies merely a few pixels in the image. After the gas size expands, it is easier to analyze as an interesting anomalous feature. Our algorithm includes techniques such as the improved K-Means classification, Spectral Angle Mapper (SAM), match filter and tracking; in the paper we will show results based on real data taken by the "FIRST" camera (Field-portable Imaging Radiometric Spectrometer Technology).

Original languageEnglish
Title of host publication2006 IEEE 24th Convention of Electrical and Electronics Engineers in Israel, IEEEI
Pages285-289
Number of pages5
DOIs
StatePublished - 1 Dec 2006
Event2006 IEEE 24th Convention of Electrical and Electronics Engineers in Israel, IEEEI - Eilat, Israel
Duration: 15 Nov 200617 Nov 2006

Publication series

NameIEEE Convention of Electrical and Electronics Engineers in Israel, Proceedings

Conference

Conference2006 IEEE 24th Convention of Electrical and Electronics Engineers in Israel, IEEEI
Country/TerritoryIsrael
CityEilat
Period15/11/0617/11/06

Keywords

  • Anomaly tracking
  • Hyperspectral data
  • Multispectral data
  • Remote sensing

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials

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