Full Content is available to subscribers

Subscribe/Learn More  >
Proceedings Article

A hyperspectral model for target detection

[+] Author Affiliations
Mark Bernhardt, Catherine Cowell, Moira Smith

Waterfall Solutions Ltd. (United Kingdom)

Phil Clare

Defence Science and Technology Lab. (United Kingdom)

Proc. SPIE 6565, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIII, 65650F (May 07, 2007); doi:10.1117/12.719363
Text Size: A A A
From Conference Volume 6565

  • Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIII
  • Sylvia S. Shen; Paul E. Lewis
  • Orlando, Florida, USA | April 09, 2007

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.

© (2007) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
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 (May 07, 2007); doi:10.1117/12.719363; http://dx.doi.org/10.1117/12.719363


Access This Proceeding
Sign in or Create a personal account to Buy this proceeding ($15 for members, $18 for non-members).

Figures

Tables

NOTE:
Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Book Chapters

Topic Collections

Advertisement
  • Don't have an account?
  • Subscribe to the SPIE Digital Library
  • Create a FREE account to sign up for Digital Library content alerts and gain access to institutional subscriptions remotely.
Access This Proceeding
Sign in or Create a personal account to Buy this proceeding ($15 for members, $18 for non-members).
Access This Proceeding
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
Access This Chapter

Access to SPIE eBooks is limited to subscribing institutions and is not available as part of a personal subscription. Print or electronic versions of individual SPIE books may be purchased via SPIE.org.