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Hyperspectral data acquisition and analysis in imaging and real-time active MIR backscattering spectroscopy

 
: Jarvis, Jan-Philip; Härtelt, Marko; Hugger, Stefan; Butschek, Lorenz; Fuchs, Frank; Ostendorf, Ralf; Wagner, Joachim; Beyerer, Juergen

:
Volltext urn:nbn:de:0011-n-4458062 (1.1 MByte PDF)
MD5 Fingerprint: 5715a7e2c9c38b66f722b58c3c0e7e09
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Erstellt am: 30.5.2017


Advanced Optical Technologies 6 (2017), Nr.2, S.83-93
ISSN: 2192-8584
ISSN: 2192-8576
European Commission EC
H2020; 645535; CHEQUERS
Compact High pErformance QUantum cascadE laseR Sensors
Englisch
Zeitschriftenaufsatz, Elektronische Publikation
Fraunhofer IAF ()
Fraunhofer IOSB ()
active stand-off spectroscopy; hyperspectral data analysis; QCL; Key Publication

Abstract
In this work we present data analysis algorithms for detection of hazardous substances in hyperspectral observations acquired using active mid-infrared (MIR) backscattering spectroscopy. We present a novel background extraction algorithm based on the adaptive target generation process proposed by Ren and Chang called the adaptive background generation process (ABGP) that generates a robust and physically meaningful set of background spectra for operation of the well-known adaptive matched subspace detection (AMSD) algorithm. It is shown that the resulting AMSD-ABGP detection algorithm competes well with other widely used detection algorithms. The method is demonstrated in measurement data obtained by two fundamentally different active MIR hyperspectral data acquisition devices. A hyperspectral image sensor applicable in static scenes takes a wavelength sequential approach to hyperspectral data acquisition, whereas a rapid wavelength-scanning single-element detector variant of the same principle uses spatial scanning to generate the hyperspectral observation. It is shown that the measurement timescale of the latter is sufficient for the application of the data analysis algorithms even in dynamic scenarios.

: http://publica.fraunhofer.de/dokumente/N-445806.html