Comparison of longwave infrared hyperspectral target detection methods

Nathan P. Wurst; Seung Hwan An; Joseph Meola

doi:10.1117/12.2518638

14 May 2019 Comparison of longwave infrared hyperspectral target detection methods

Nathan P. Wurst, Seung Hwan An, Joseph Meola

Proceedings Volume 10986, Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imagery XXV; 1098617 (2019) https://doi.org/10.1117/12.2518638
Event: SPIE Defense + Commercial Sensing, 2019, Baltimore, MD, United States

Abstract

Numerous methods exist to perform hyperspectral target detection. Application of these algorithms often requires the data to be atmospherically corrected. Detection for longwave infrared data typically requires surface temperature estimates as well. This work compares the relative robustness of various target detection algorithms with respect to atmospheric compensation and target temperature uncertainty. Specifically, the adaptive coherence estimator and spectral matched filter will be compared with subspace detectors for various methods of atmospheric compensation and temperature-emissivity separation. Comparison is performed using both daytime and nighttime longwave infrared hyperspectral data collected at various altitudes for various target materials.

Conference Presentation

Citation Download Citation

Nathan P. Wurst, Seung Hwan An, and Joseph Meola "Comparison of longwave infrared hyperspectral target detection methods", Proc. SPIE 10986, Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imagery XXV, 1098617 (14 May 2019); https://doi.org/10.1117/12.2518638

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