Different Bayesian Network Models in the Classification of Remote Sensing Images
نویسندگان
چکیده
In this paper we study the application of Bayesian network models to classify multispectral and hyperspectral remote sensing images. Different models of Bayesian networks as: Naive Bayes (NB), Tree Augmented Naive Bayes (TAN) and General Bayesian Networks (GBN), are applied to the classification of hyperspectral data. In addition, several Bayesian multi-net models: TAN multi-net, GBN multi-net and the model developed by Gurwicz and Lerner, TAN-Based Bayesian ClassMatched multi-net (tBCM) (see [1]) are applied to the classification of multispectral data. A comparison of the results obtained with the different classifiers is done.
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