Scene analysis and detection in thermal infrared remote sensing using independent component analysis

Bernard R. Foy; James Theiler

doi:10.1117/12.542442

12 April 2004 Scene analysis and detection in thermal infrared remote sensing using independent component analysis

Bernard R. Foy, James Theiler

Proceedings Volume 5439, Independent Component Analyses, Wavelets, Unsupervised Smart Sensors, and Neural Networks II; (2004) https://doi.org/10.1117/12.542442
Event: Defense and Security, 2004, Orlando, Florida, United States

Abstract

Independent Component Analysis can be used to analyze cluttered scenes from remote sensing imagery and to detect objects. We show examples in the thermal infrared spectral region (8-12 μm) using both passive hyperspectral data and active multispectral data. The examples are from actual field data and computer simulations. ICA isolates spectrally distinct objects with nearly one-to-one correspondence with the independent component basis functions, making it useful for modeling the clutter in typical scenes. We show examples of chemical plume detection in real and simulated data.

Citation Download Citation

Bernard R. Foy and James Theiler "Scene analysis and detection in thermal infrared remote sensing using independent component analysis", Proc. SPIE 5439, Independent Component Analyses, Wavelets, Unsupervised Smart Sensors, and Neural Networks II, (12 April 2004); https://doi.org/10.1117/12.542442

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