高光谱成像
化学成像
遥感
像素
光辉
图像传感器
探测器
计算机科学
成像光谱仪
光学
分光计
扫描仪
图像处理
材料科学
计算机视觉
人工智能
物理
地质学
图像(数学)
作者
Julia R. Dupuis,John P. Dixon,Elizabeth Schundler,S. Chase Buchanan,J. D. Rameau,David J. Mansur,Henry Kvinge,Elin Farnell,Christopher Peterson,Michael Kirby
摘要
A compressive sensing hyperspectral imaging (CS-HSI) platform has been developed for low-cost, standoff, wide area Early Warning of chemical vapor plumes. The sensor, operating in the longwave infrared (LWIR) spectral range with a single-pixel architecture, simultaneously addresses two practical shortcomings of LWIR chemical plume imaging platforms: (1) the single pixel architecture enables an order of magnitude cost reduction relative to HSI sensors employing a cooled focal plane array or high-speed gimbaled scanner, and (2) the inherent imaging modality achieves a favorable pixel fill factor and associated probability of detection for relevant chemical threats relative to single pixel scanned sensors. The CS-HSI employs a low-cost digital micromirror device modified for use in the LWIR spectral range to spatially encode an image of the scene. An LWIR spectrometer employing a tunable Fabry-Perot filter and a mercury cadmium telluride single element photo-detector spectrally resolves the spatially integrated image while mitigating instrument radiance. A CS processing module reconstructs the spatially compressed hyperspectral image where the measurement and sparsity basis functions are specifically tailored to the CS-HSI hardware and chemical plume imaging. An automated target recognition algorithm is applied to the reconstructed hyperspectral data employing a variant of the Adaptive Cosine Estimator for the detection of the chemical plumes in cluttered and dynamic backgrounds. The development, characterization, and a series of capability demonstrations of a prototype CS-HSI sensor are presented. Capability demonstrations include chemical plume imaging of R-134 at mission-relevant concentration pathlength product levels in a laboratory setting.
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