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Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Editor: James C. Wyant
  • Vol. 47, Iss. 28 — Oct. 1, 2008
  • pp: F96–F106

Statistical characterization of hyperspectral background clutter in the reflective spectral region

Dimitris Manolakis, Michael Rossacci, Denise Zhang, John Cipar, Ronald Lockwood, Thomas Cooley, and John Jacobson  »View Author Affiliations


Applied Optics, Vol. 47, Issue 28, pp. F96-F106 (2008)
http://dx.doi.org/10.1364/AO.47.000F96


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Abstract

Hyperspectral imaging systems for daylight operation measure and analyze reflected and scattered radiation in p-spectral channels covering the reflective infrared region 0.4 2.5 μm . Consequently, the p-dimensional joint distribution of background clutter is required to design and evaluate optimum hyperspectral imaging processors. In this paper, we develop statistical models for the spectral variability of natural hyperspectral backgrounds using the class of elliptically contoured distributions. We demonstrate, using data from the NASA AVIRIS sensor, that models based on the multivariate t-elliptically contoured distribution capture with sufficient accuracy the statistical characteristics of natural hyperspectral backgrounds that are relevant to target detection applications.

© 2008 Optical Society of America

OCIS Codes
(280.0280) Remote sensing and sensors : Remote sensing and sensors
(300.0300) Spectroscopy : Spectroscopy

ToC Category:
Hyperspectral Processing and Analysis

History
Original Manuscript: March 4, 2008
Revised Manuscript: May 23, 2008
Manuscript Accepted: July 28, 2008
Published: August 7, 2008

Virtual Issues
Vol. 3, Iss. 12 Virtual Journal for Biomedical Optics

Citation
Dimitris Manolakis, Michael Rossacci, Denise Zhang, John Cipar, Ronald Lockwood, Thomas Cooley, and John Jacobson, "Statistical characterization of hyperspectral background clutter in the reflective spectral region," Appl. Opt. 47, F96-F106 (2008)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-47-28-F96

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