Paper
22 October 2013 Efficient implementations of hyperspectral chemical-detection algorithms
Cory J. C. Brett, Robert S. DiPietro, Dimitris G. Manolakis, Vinay K. Ingle
Author Affiliations +
Abstract
Many military and civilian applications depend on the ability to remotely sense chemical clouds using hyperspectral imagers, from detecting small but lethal concentrations of chemical warfare agents to mapping plumes in the aftermath of natural disasters. Real-time operation is critical in these applications but becomes diffcult to achieve as the number of chemicals we search for increases. In this paper, we present efficient CPU and GPU implementations of matched-filter based algorithms so that real-time operation can be maintained with higher chemical-signature counts. The optimized C++ implementations show between 3x and 9x speedup over vectorized MATLAB implementations.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Cory J. C. Brett, Robert S. DiPietro, Dimitris G. Manolakis, and Vinay K. Ingle "Efficient implementations of hyperspectral chemical-detection algorithms", Proc. SPIE 8897, Electro-Optical Remote Sensing, Photonic Technologies, and Applications VII; and Military Applications in Hyperspectral Imaging and High Spatial Resolution Sensing, 88970T (22 October 2013); https://doi.org/10.1117/12.2028562
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Sensors

MATLAB

Mahalanobis distance

C++

Clouds

Detection and tracking algorithms

Hyperspectral imaging

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