Johnson distribution models of hyperspectral image data clusters

Eduardo C. Meidunas; Steven C. Gustafson

doi:10.1117/12.663965

4 May 2006 Johnson distribution models of hyperspectral image data clusters

Eduardo C. Meidunas, Steven C. Gustafson

Proceedings Volume 6233, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XII; 623322 (2006) https://doi.org/10.1117/12.663965
Event: Defense and Security Symposium, 2006, Orlando (Kissimmee), Florida, United States

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.

Citation Download Citation

Eduardo C. Meidunas and Steven C. Gustafson "Johnson distribution models of hyperspectral image data clusters", Proc. SPIE 6233, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XII, 623322 (4 May 2006); https://doi.org/10.1117/12.663965

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