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Proceedings Paper

LWIR change detection using robustified temperature emissivity separation and alpha residuals
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Paper Abstract

In this paper, we consider change detection in the longwave infrared (LWIR) domain. Because thermal emission is the dominant radiation source in this domain, differences in temperature may appear as material changes and introduce false alarms in change imagery. Existing methods, such as temperature-emissivity separation and alpha residuals, attempt to extract temperature-independent LWIR spectral information. However, both methods remain susceptible to residual temperature effects which degrade change detection performance. Here, we develop temperature-robust versions of these algorithms that project the spectra into approximately temperatureinvariant subspaces. The complete error covariance matrix for each method is also derived so that Mahalanobis distance may be used to quantify spectral differences in the temperature-invariant domain. Examples using synthetic and measured data demonstrate substantial performance improvement relative to the baseline algorithms.

Paper Details

Date Published: 14 May 2019
PDF: 11 pages
Proc. SPIE 10986, Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imagery XXV, 1098603 (14 May 2019); doi: 10.1117/12.2519192
Show Author Affiliations
Nicholas Durkee, Wright State Univ. (United States)
Joshua N. Ash, Wright State Univ. (United States)
Joseph Meola, Air Force Research Lab. (United States)

Published in SPIE Proceedings Vol. 10986:
Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imagery XXV
Miguel Velez-Reyes; David W. Messinger, Editor(s)

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