Regularized covariance estimators for hyperspectral data classification and its application to feature extraction

International Geoscience and Remote Sensing Symposium (IGARSS)

Volumn 6, Issue , 2002, Pages 3510-3512

  Kuo, Bor Chen ^a   Landgrebe, David A ^a  

^a NATIONAL TAICHUNG UNIVERSITY OF EDUCATION   (Taiwan)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTER SIMULATION; FEATURE EXTRACTION; MATHEMATICAL MODELS; MATRIX ALGEBRA; MAXIMUM LIKELIHOOD ESTIMATION; OPTIMIZATION; PROBABILITY; STATISTICAL METHODS;

BAYESIAN LEAVE-ONE-OUT COVARIANCE ESTIMATOR; DISCRIMINANT ANALYSIS FEATURE EXTRACTION; HYPERSPECTRAL DATA CLASSIFICATION; MIXED LEAVE-ONE-OUT COVARIANCE ESTIMATOR;

INFRARED IMAGING;

EID: 0036399415     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (5)

1. J.H. Friedman, "Regularized Discriminant Analysis," Journal of the American Statistical Association, vol. 84, pp. 165-175, March 1989
2. J. P. Hoffbeck and D.A. Landgrebe, "Covariance matrix estimation and classification with limited training data" IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 18, No. 7, pp. 763-767, July 1996.
3. S. Tadjudin and D.A. Landgrebe, Classification of High Dimensional Data with Limited Training Samples, Purdue University, West Lafayette, IN., TR-EE 98-8, April, 1998, pp35-82.
4. B-C. Kuo, Improved Statistics Estimation and Feature Extraction for Hyperspectral Data Classification. Ph.D. thesis. Purdue University, December 2001
5. W. Rayens and T. Greene, "Covariance pooling and stabilization for classification." Computational Statistics and Data Analysis, vol. 11, pp. 17-42, 1991