TY - CHAP
T1 - One-Class SVMs for Hyperspectral Anomaly Detection
AU - Banerjee, Amit
AU - Burlina, Philippe
AU - Diehl, Chris
PY - 2009/11/4
Y1 - 2009/11/4
KW - Computational and detection performance of SVDD anomaly detectors
KW - Goodness-of-fit test statistic for hyperspectral imagery based on Barringhaus, Henze, Epps and Pully (BHEP) test
KW - Normalized metric appropriate for anomaly detection in spectral imagery
KW - One-class SVMs for hyperspectral anomaly detection
KW - SVDD algorithms for hyperspectral anomaly detection
KW - SVDD derivation
KW - SVDD function optimization
KW - Support Vector Data Description (SVDD)
KW - Support vector framework for hyperspectral anomaly detection
UR - http://www.scopus.com/inward/record.url?scp=84856173037&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84856173037&partnerID=8YFLogxK
U2 - 10.1002/9780470748992.ch8
DO - 10.1002/9780470748992.ch8
M3 - Chapter
AN - SCOPUS:84856173037
SN - 9780470722114
SP - 169
EP - 192
BT - Kernel Methods for Remote Sensing Data Analysis
PB - John Wiley & Sons, Ltd
ER -