The Study on Remote Sensing Data Classification Using Bayesian Network

Dai Qin; Ma Jian-wen; Li Qi-qing; Chen-Xue; Feng Chun

Volume 27 Issue 11

Nov. 2005

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Dai Qin, Ma Jian-wen, Li Qi-qing, Chen-Xue, Feng Chun. The Study on Remote Sensing Data Classification Using Bayesian Network[J]. Journal of Electronics & Information Technology, 2005, 27(11): 1782-1785.

Citation:

Dai Qin, Ma Jian-wen, Li Qi-qing, Chen-Xue, Feng Chun. The Study on Remote Sensing Data Classification Using Bayesian Network[J]. Journal of Electronics & Information Technology, 2005, 27(11): 1782-1785.

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The Study on Remote Sensing Data Classification Using Bayesian Network

Received Date: 2004-06-01
Rev Recd Date: 2005-01-13
Publish Date: 2005-11-19

Abstract

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.

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References(1)

References

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