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14 May 2019 LWIR change detection using robustified temperature emissivity separation and alpha residuals
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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.
Conference Presentation
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Nicholas Durkee, Joshua N. Ash, and Joseph Meola "LWIR change detection using robustified temperature emissivity separation and alpha residuals", Proc. SPIE 10986, Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imagery XXV, 1098603 (14 May 2019); https://doi.org/10.1117/12.2519192
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