Share Email Print
cover

Proceedings Paper

Johnson distribution models of hyperspectral image data clusters
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

The Johnson System for characterizing an empirical distribution is used to model the non-normal behavior of Mahalanobis distances in material clusters extracted from hyperspectral imagery data. An automated method for determining Johnson distribution parameters is used to model Mahalanobis distance distributions and is compared to an existing method which uses mixtures of F distributions. The results lead to a method for determining outliers and mitigating their effects.

Paper Details

Date Published: 4 May 2006
PDF: 13 pages
Proc. SPIE 6233, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XII, 623322 (4 May 2006); doi: 10.1117/12.663965
Show Author Affiliations
Eduardo C. Meidunas, Air Force Institute of Technology (United States)
Steven C. Gustafson, Air Force Institute of Technology (United States)


Published in SPIE Proceedings Vol. 6233:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XII
Sylvia S. Shen; Paul E. Lewis, Editor(s)

© SPIE. Terms of Use
Back to Top