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Proceedings Paper

Characterizing the temporal and spatial variability of longwave infrared spectral images of targets and backgrounds
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Paper Abstract

Following the public release of the Spectral and Polarimetric Imagery Collection Experiment (SPICE) dataset, a persistent imaging experiment dataset collected by the Army Research Laboratory (ARL), the data were analyzed and materials in the scene characterized temporally and spatially using radiance data. The noise equivalent spectral radiance provided by the sensor manufacturer was compared with instrument noise calculated from in-scene information, and found to be comparable given differences in laboratory setting and real-life conditions. The processed dataset have regular "inconsistent cubes," specifically for data collected immediately after blackbody measurements, which were automatically executed approximately at each hour mark. Omitting these erroneous data, three target detection algorithms (adaptive coherent/cosine estimator, spectral angle mapper, and spectral matched filter) were tested on the temporal data using two target spectra (noon and midnight). The spectral matched filter produced the best detection rate for both noon and midnight target spectra for a 24-hrs period.

Paper Details

Date Published: 5 May 2017
PDF: 11 pages
Proc. SPIE 10198, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIII, 101980K (5 May 2017); doi: 10.1117/12.2262506
Show Author Affiliations
Nirmalan Jeganathan, Rochester Institute of Technology (United States)
John Kerekes, Rochester Institute of Technology (United States)
Dalton Rosario, U.S. Army Research Lab. (United States)

Published in SPIE Proceedings Vol. 10198:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIII
Miguel Velez-Reyes; David W. Messinger, Editor(s)

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