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《Journal of Data Acquisition and Processing》 2011-04
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Unsupervised Change Detection for Multichannnel Remote Sensing Images Based on FCM and Neighborhood Analysis

Zhao Lei1,Wang Bin1,2,Zhang Liming1(1.Department of Electronic Engineering,Fudan University,Shanghai,200433,China;2.The Key Laboratory of Wave Scattering and Remote Sensing Information,Fudan University,Shanghai,200433,China)  
An unsupervised change detection method based on fuzzy C-means(FCM) clustering and neighborhood analysis is proposed.Usual change detection methods compress the change information into one-dimension change image, resulting in the loss of original multispectral information.Hence, the FCM method is introduced into the change detection problem of multichannel remote sensing images.However,the FCM method is sensitive to the isolated point,and its clustering result can be influenced by noise.Based on the FCM method,a new method combining FCM with neighborhood analysis is also proposed for unsupervised change detection in multichannel remote sensing images.Experimental results demonstrate that the proposed method can remove the influence of noise from the FCM algorithm and detect change information accurately.
【Fund】: 国家自然科学基金(61071134)资助项目;; 国家高技术研究发展计划(“八六三计划”)(2009AA12Z115)资助项目
【CateGory Index】: TP751
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