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Hyperspectral image analysis for standoff trace detection using IR laser spectroscopy

 
: Jarvis, J.P.; Fuchs, F.; Hugger, S.; Ostendorf, R.; Butschek, L.; Yang, Q.; Dreyhaupt, A.; Grahmann, J.; Wagner, J.

:

Fountain, A.W. (Ed.) ; Society of Photo-Optical Instrumentation Engineers -SPIE-, Bellingham/Wash.:
Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XVII : 18-20 April 2016, Baltimore, Maryland, United States
Bellingham, WA: SPIE, 2016 (Proceedings of SPIE 9824)
ISBN: 9781510600652
Paper 98240V, 10 pp.
Conference "Chemical, Biological, Radiological, Nuclear, and Explosives Sensing" (CBRNE) <17, 2016, Baltimore/Md.>
English
Conference Paper
Fraunhofer IAF ()
Fraunhofer IPMS ()

Abstract
In the recent past infrared laser backscattering spectroscopy using Quantum Cascade Lasers (QCL) emitting in the molecular fingerprint region between 7.5 um and 10 um proved a highly promising approach for stand-off detection of dangerous substances. In this work we present an active illumination hyperspectral image sensor, utilizing QCLs as spectral selective illumination sources. A high performance Mercury Cadmium Telluride (MCT) imager is used for collection of the diffusely backscattered light. Well known target detection algorithms like the Adaptive Matched Subspace Detector and the Adaptive Coherent Estimator are used to detect pixel vectors in the recorded hyperspectral image that contain traces of explosive substances like PETN, RDX or TNT. In addition we present an extension of the backscattering spectroscopy technique towards real-time detection using a MOEMS EC-QCL.

: http://publica.fraunhofer.de/documents/N-413263.html