The Study on Remote Sensing Data Classification Using Bayesian Network
Dai Qin①; Ma Jian-wen①; Li Qi-qing①; Chen-Xue①②; Feng Chun③
①Institute of Remote Sensing Applications, CAS, Beijing 100101, China;②Department of Resources and Environment Science, Beijing Normal University,Beijing100875,China;③Institute of Land Resources and High Techniques, China University of Geosciences, Beijing 100083, China
Abstract：Because of the complexity in satellite remote sensing imaging system, some uncertainties or mixed spectrum information are contained in the data. By using maximal likelihood classification to process remote sensing data, the result accuracy of the classification is affected. In order to improve the accuracy of the classification, prior knowledge is needed to modify the probability. Bayesian network is composed of directed acyclic graph and probability chart; it can modify the prior probability density dynamically and improve the accuracy of classification. In this paper, a technical procedure is demonstrated that using Bayesian network to process the remote sensing data, the classification results prove that Bayesian network has solid mathematics base and can be a new effective methods for remote sensing data processing.
戴 芹; 马建文; 李启青; 陈 雪; 冯春. 遥感数据的贝叶斯网络分类研究[J]. 电子与信息学报, 2005, 27(11): 1782-1785 .
Dai Qin①; Ma Jian-wen①; Li Qi-qing①; Chen-Xue①②; Feng Chun③. The Study on Remote Sensing Data Classification Using Bayesian Network. , 2005, 27(11): 1782-1785 .
2005, Vol. 27 
