Performance comparison of hyperspectral target detection algorithms in altitude varying scenes

Adam P. Cisz; John R. Schott

doi:10.1117/12.603768

1 June 2005 Performance comparison of hyperspectral target detection algorithms in altitude varying scenes

Adam P. Cisz, John R. Schott

Proceedings Volume 5806, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XI; (2005) https://doi.org/10.1117/12.603768
Event: Defense and Security, 2005, Orlando, Florida, United States

Abstract

Many different hyperspectral target detection algorithms have been developed and tested under various assumptions, methods, and data sets. This work examines the spectral angle mapper (SAM), adaptive coherence estimator (ACE), and constrained energy maximization (CEM) algorithms. Algorithm performance is examined over multiple images, targets, and backgrounds. Methods to examine algorithm performance are plentiful and several different metrics are used here. Quantitative metrics are used to make direct comparisons between algorithms. Further analysis using visual performance metrics is made to examine interesting trends in the data. Results show an increase in detection algorithm performance as image altitude increases and spatial information decreases. Theories to explain this phenomenon are introduced.

Citation Download Citation

Adam P. Cisz and John R. Schott "Performance comparison of hyperspectral target detection algorithms in altitude varying scenes", Proc. SPIE 5806, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XI, (1 June 2005); https://doi.org/10.1117/12.603768

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