Different Bayesian Network Models in the Classification of Remote Sensing Images

نویسندگان

  • Cristina Solares
  • Ana Maria Sanz
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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تاریخ انتشار 2007