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.

Date Published: 14 May 2019
PDF: 12 pages
Proc. SPIE 10986, Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imagery XXV, 1098617 (14 May 2019); doi: 10.1117/12.2518638

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