DING Yuqi, SHAO Zhenfeng, HU Shiyuan. Combined with Cloud Model and EM Clustering for Remote Sensing Image Segmentation[J]. Geomatics and Information Science of Wuhan University, 2015, 40(6): 721-726. DOI: 10.13203/j.whugis20130483
Citation:
DING Yuqi, SHAO Zhenfeng, HU Shiyuan. Combined with Cloud Model and EM Clustering for Remote Sensing Image Segmentation[J]. Geomatics and Information Science of Wuhan University, 2015, 40(6): 721-726. DOI: 10.13203/j.whugis20130483
DING Yuqi, SHAO Zhenfeng, HU Shiyuan. Combined with Cloud Model and EM Clustering for Remote Sensing Image Segmentation[J]. Geomatics and Information Science of Wuhan University, 2015, 40(6): 721-726. DOI: 10.13203/j.whugis20130483
Citation:
DING Yuqi, SHAO Zhenfeng, HU Shiyuan. Combined with Cloud Model and EM Clustering for Remote Sensing Image Segmentation[J]. Geomatics and Information Science of Wuhan University, 2015, 40(6): 721-726. DOI: 10.13203/j.whugis20130483
1State Key Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing,;(Wuhan University,Wuhan 430079,China;2School of Resource and Environmental Sciences,Wuhan University,Wuhan 430079,China
Funds: The National Key Basic Research Program(973Program),No.2010CB731800;the National Natural Science Foun-dation of China,No.61172174;the National Key Scientific Instrument and Equipment Development,No.2012YQ16018505;the Key
To solve the shortcomings of the traditional hierarchical clustering algorithm for remotesensing image segmentation,in this paper we propose a new algorithm based on a cloud model and EMalgorithm.In the proposed algorithm,we extract the bottom concepts from the remote sensing imageusing apeak method for cloud transform,and get higher cloud concepts through the EM algorithm,and finally segment the image with Great Criterion.The results show that clustering concepts can beclassified quickly as a specified number by the EM algorithm for estimatation of the mathematical fea-tures of the higher clouds.The proposed algorithm is superior to the traditional methods.
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