Nonparametric framework for detecting spectral anomalies in hyperspectral images

IEEE Geoscience and Remote Sensing Letters

Volumn 8, Issue 4, 2011, Pages 666-670

  Veracini, Tiziana ^a   Matteoli, Stefania ^a   Diani, Marco ^a   Corsini, Giovanni ^a  

^a UNIVERSITY OF PISA   (Italy)

Author keywords

Anomaly detection (AD); hyperspectral images; kernel bandwidth estimation; Parzen windows

Indexed keywords

ANOMALY DETECTION; BANDWIDTH MATRIX; BANDWIDTH SELECTIONS; BAYESIAN APPROACHES; HYPER-SPECTRAL IMAGES; HYPERSPECTRAL DATA; KERNEL BANDWIDTH ESTIMATION; LIKELIHOOD RATIO TESTS; NON-PARAMETRIC; PARZEN WINDOWING; PARZEN WINDOWS; PDF ESTIMATION; PROBABILITY DENSITY FUNCTION (PDF); REMOTELY SENSED IMAGES; SPECTRAL ANOMALIES; STATISTICAL MODELS; UNSUPERVISED METHOD;

BANDWIDTH; BAYESIAN NETWORKS; ESTIMATION; REMOTE SENSING;

PROBABILITY DENSITY FUNCTION;

EID: 79959707164     PISSN: 1545598X     EISSN: None     Source Type: Journal    
DOI: 10.1109/LGRS.2010.2099103     Document Type: Article

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