利用互信息改进遥感影像朴素贝叶斯网络分类器
An Improvement of Naive Bayesian Network Classifier for Remote Sensing Images Based on Mutual Information
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摘要: 针对朴素贝叶斯网络简单条件独立性假设的不足,将它的一种改进形式——选择型朴素贝叶斯网络和两种扩展形式(树增强型朴素贝叶斯网络、贝叶斯增强型朴素贝叶斯网络)用于多光谱遥感影像的分类中。在分析波段间互信息的基础上,分别构造了上述3种分类器,并和朴素贝叶斯网络分类器的性能进行了比较。Abstract: This paper proposes an improvement of Naive Bayesian classifier-selective Naive Baysian classifier together with two enhancement of Naive Bayesian classifier-tree Augmented Nave Bayes and Bayes Augmented Nave Bayes.We constructed these classifiers for remote sensing images based on the mutual information between bands,and compared their performance with the NBC.
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