Logistic discrimination between classes with nearly equal spectral response in high dimensionality

Logistic discrimination can be regarded as a partially parametric approach to pattern recognition. The method is quite general and robust: it assumes nothing about the probability distribution of variables and requires the estimation of fewer parameters than some better-known procedures such as the...

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Bibliographic Details
Published inIGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477) Vol. 6; pp. 3748 - 3750 vol.6
Main Authors Bittencourt, H.R., Clarke, R.T.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2003
Subjects
Biological system modeling
Covariance matrix
Digital images
Image sensors
Logistics
Maximum likelihood estimation
Parameter estimation
Pattern recognition
Probability distribution
Robustness
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Summary:Logistic discrimination can be regarded as a partially parametric approach to pattern recognition. The method is quite general and robust: it assumes nothing about the probability distribution of variables and requires the estimation of fewer parameters than some better-known procedures such as the Gaussian maximum likelihood discriminator. This paper describes the logistic discrimination model and gives results obtained when using it to classify an AVIRIS image with classes that are spectrally very similar.
ISBN:9780780379299
0780379292
DOI:10.1109/IGARSS.2003.1295257