Detection of occluded targets using thermal imaging spectroscopy

M. Shimoni, Christiaan Perneel, J. P. Gagnon

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

Abstract

Automatic detection of occluded targets from a sequence of images is an interesting area of research for defense related application. In this paper, change detection methods are investigated for the detection of buried improvised explosive devices (IED) using temporal thermal hyperspectral scenes. Specifically, the paper assesses the detection of buried small aluminium plates using the TELOPS Hyper-Cam sensor and by applying two change detection algorithms: multivariate statistical based method (Cross-Covariance (CC)) and class-conditional change detector (QCC). It was found that spectral based change detection is a good method for the detection of buried IED under disturbed soil. Moreover, the Cross-Covariance (CC)) and the class-conditional (QCC) change detector were able to detect changes using short temporal sequences as long temporal sequences pairs.

Original languageEnglish
Title of host publication2nd Workshop on Hyperspectral Image and Signal Processing
Subtitle of host publicationEvolution in Remote Sensing, WHISPERS 2010 - Workshop Program
DOIs
Publication statusPublished - 2010
Event2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2010 - Reykjavik, Iceland
Duration: 14 Jun 201016 Jun 2010

Publication series

Name2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2010 - Workshop Program

Conference

Conference2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2010
Country/TerritoryIceland
CityReykjavik
Period14/06/1016/06/10

Keywords

  • Buried object
  • Change detection
  • Improvised explosive devices (IED)
  • Thermal hyperspectral

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