A hyperspectral model for target detection

Mark Bernhardt; Phil Clare; Catherine Cowell; Moira Smith

doi:10.1117/12.719363

7 May 2007 A hyperspectral model for target detection

Mark Bernhardt, Phil Clare, Catherine Cowell, Moira Smith

Proceedings Volume 6565, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIII; 65650F (2007) https://doi.org/10.1117/12.719363
Event: Defense and Security Symposium, 2007, Orlando, Florida, United States

Abstract

In this paper an end-to-end hyperspectral imaging system model is described which has the ability to predict the performance of hyperspectral imaging sensors in the visible through to the short-wave infrared regime for sub-pixel targets. The model represents all aspects of the system including the target signature and background, the atmosphere, the optical and electronic properties of the imaging spectrometer, as well as details of the processing algorithms employed. It provides an efficient means of Monte-Carlo modelling for sensitivity analysis of model parameters over a wide range. It is also capable of representing certain types of non-Gaussian hyperspectral clutter arising from heterogeneous backgrounds. The capabilities of the model are demonstrated in this paper by considering Uninhabited Airborne Vehicle scenarios and comparing both multispectral and hyperspectral sensors. Both anomaly detection and spectral matched-filter algorithms are characterised in terms of Receiver Operating Characteristic curves. Finally, some results from a preliminary validation exercise are presented.

Citation Download Citation

Mark Bernhardt, Phil Clare, Catherine Cowell, and Moira Smith "A hyperspectral model for target detection", Proc. SPIE 6565, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIII, 65650F (7 May 2007); https://doi.org/10.1117/12.719363

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