Selecting training and test images for optimized anomaly detection algorithms in hyperspectral imagery through robust parameter design

Authors

Frank M. Mindrup, Air Force Institute of Technology
Mark A. Friend, Air Force Institute of Technology
Kenneth W. Bauer, Air Force Institute of Technology

Document Type

Conference Proceeding

Publication Date

5-20-2011

Comments

Copyright © 2011 Society of Photo-Optical Instrumentation Engineers (SPIE)

Co-author F. Mindrup was enrolled in an AFIT PhD program at the time of this conference. (AFIT-DS-ENS-11-04, October 2011)

Event: SPIE Defense, Security, and Sensing, 2011, Orlando

DOI

10.1117/12.884120

Source Publication

Proceedings of SPIE Volume 8048: Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVII

Recommended Citation

Frank M. Mindrup, Mark A. Friend, and Kenneth W. Bauer "Selecting training and test images for optimized anomaly detection algorithms in hyperspectral imagery through robust parameter design", Proc. SPIE 8048, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVII, 80480C (20 May 2011); https://doi.org/10.1117/12.884120