Statistical characterization of hyperspectral background clutter in the reflective spectral region.
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 microm. 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.
Manolakis
Dimitris
D
MIT Lincoln Laboratory, 244 Wood Street, Lexington, Massachusetts 02420, USA. dmanolakis@ll.mit.edu
Rossacci
Michael
M
Zhang
Denise
D
Cipar
John
J
Lockwood
Ronald
R
Cooley
Thomas
T
Jacobson
John
J