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《Acta Automatica Sinica》 2008-03
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Object-level Change Detection Based on Multiscale Fusion

HUO Chun-Lei~1 CHENG Jian~1 LU Han-Qing~1 ZHOU Zhi-Xin~(1,2) 1.National Laboratory of Pattern Recognition,Institute of Automation,Chinese Academy of Sciences,Beijing 100080 2.Beijing Institute of Remote Sensing,Beijing 100854  
Urban change detection based on multiscale fusion is discussed in this paper.The limitations of traditional change detection methods and the difficulties of urban change detection of very high resolution images are first analyzed. To address the above limitations,a novel object-level framework based on multiseale fusion is presented for urban change detection.Taking advantages of the object-level change detection,the framework can improve the separability of changed class and unchanged class.To further improve the change detection accuracy,two different multiscale fusion strategies are applied in the framework.Experimental results obtained on QuickBird images confirm the effectiveness of the proposed approach.
【Fund】: 国家自然科学基金创新群体项目(60121302)资助~~
【CateGory Index】: TP751
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