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Proceedings Paper

Computational reconfigurable imaging spectrometer (CRISP)
Author(s): C. M. Wynn; Y. Rachlin; A. B. Milstein; J. Lessard; S. Kaushik; R. M. Sullenberger
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Paper Abstract

Hyperspectral imaging spectrometers are useful in numerous applications including remote sensing, environmental monitoring, surveillance, minerology and precision agriculture. Historically, high cost and complexity has limited the number of fielded hyperspectral imagers. The Computational Reconfigurable Imaging Spectrometer (CRISP) sensor is a novel hyperspectral imaging spectrometer suitable for high-resolution air or space-based missions. CRISP uses a computational imaging approach to reduce the system’s overall size and complexity. It exploits platform motion and a spectrally coded focal-plane mask to temporally modulate the optical spectrum, enabling simultaneous measurement of multiple spectral bins (i.e. multiplexing). The novel design enables high performance from smaller and less-expensive components (e.g. uncooled microbolometers), and is thus suitable for small space and air platforms. This talk discusses our demonstrator system (including recent flight results) and compares it to theory. Our flights demonstrate plume detection using an uncooled, airborne, longwave infrared CRISP imaging spectrometer. We discuss progress developing algorithms to enable spectral recovery in the presence of motion blur, utilizing the CRISP architecture to advantage. These algorithms enable a fast scanning mode, trading off computational complexity and reconstruction quality for fast area coverage rate.

Paper Details

Date Published: 21 April 2020
PDF: 10 pages
Proc. SPIE 11396, Computational Imaging V, 1139607 (21 April 2020); doi: 10.1117/12.2552937
Show Author Affiliations
C. M. Wynn, MIT Lincoln Lab. (United States)
Y. Rachlin, MIT Lincoln Lab. (United States)
A. B. Milstein, MIT Lincoln Lab. (United States)
J. Lessard, MIT Lincoln Lab. (United States)
S. Kaushik, MIT Lincoln Lab. (United States)
R. M. Sullenberger, MIT Lincoln Lab. (United States)

Published in SPIE Proceedings Vol. 11396:
Computational Imaging V
Lei Tian; Jonathan C. Petruccelli; Chrysanthe Preza, Editor(s)

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