Standoff hyperspectral imaging of explosives residues using broadly tunable external cavity quantum cascade laser illumination

被引:26
作者
Bernacki, Bruce E. [1 ]
Phillips, Mark C. [1 ]
机构
[1] Pacific NW Natl Lab, Richland, WA 99352 USA
来源
CHEMICAL, BIOLOGICAL, RADIOLOGICAL, NUCLEAR, AND EXPLOSIVES (CBRNE) SENSING XI | 2010年 / 7665卷
关键词
explosives detection; quantum cascade laser; external cavity tunable laser; hyperspectral imaging; SPECTROSCOPY;
D O I
10.1117/12.849543
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
We describe experimental results on the detection of explosives residues with active hyperspectral imaging by illumination of the target surface using an external cavity quantum cascade laser (ECQCL) and imaging using an uncooled microbolometer camera. Explosives have rich absorption features in the molecular fingerprint region that spans 1500 to 500 wavenumbers and is easily probed by the wavelength range of quantum cascade lasers (QCL), which can be fabricated to emit from 3300 to 400 wavenumbers. Our laboratory-built ECQCL consists of a Fabry-Perot laser with anti-reflection coated front facet that is arranged in a Littman-Metcalf configuration. The ECQCL was operated quasi-CW with a 100 kHz repetition rate, 50% duty cycle drive signal and tuning range from 1102.95 to 983.8 wavenumbers. The active hyperspectral imaging technique forms an image hypercube by recording one image for each tuning step of the ECQCL. For the experiments reported here, each wavelength band was 2 wavenumbers wide and 60 bands of image data were acquired in 2 seconds. The resulting hyperspectral image contains the full absorption spectrum produced by the illumination laser at each pixel in the image which can then be used to identify the explosive type and relative quantity using the rich library of spectral identification approaches developed initially in the remote sensing community. These techniques include spectral feature fitting, matched filtering, and mixture tuned matched filtering. Mixtures of materials can be evaluated using linear spectral unmixing approaches and matched filtering or mixture tuned matched filtering. We provide examples of these methods using ENVI, a commercial spectral image processing software package.
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页数:10
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