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Remote Sensing Technology and Application  2016, Vol. 31 Issue (3): 481-487    DOI: 10.11873/j.issn.1004-0323.2016.3.0481
    
Combining Super\|pixel Segmentation and Multiple Difference Maps for SAR Change Detection
Zhang Mingzhe1,2,Zhang Hong1,Wang Chao1,Liu Meng1,Xie Lei1,2
(1 Key Laboratory of Digital Earth Science,Institute of Remote Sensing and Digital Earth,
Chinese Academy of Sciences,Beijing 100094,China;
2.University of Chinese Academy of Sciences,Beijing 100049,China)
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Abstract  

The traditional pixel\|based change detection methods give high false alarm rate and broken areas.In order to solve this problem,we present a novel change detection method that combines a segmentation approach and three pixel\|based Difference Maps (DM).In this paper,the Simple Linear Iterative Clustering (SLIC) super\|pixel segmentation is introduced into SAR images segmentation,which can preserve edges between different land cover types and perform on two SAR images simultaneously.Meanwhile,three pixel\|based DMs are utilized to gain the initial change masks.Then,the majority voting is utilized for the fusion of segmentation result and initial change masks.Two Radarsat\|2 images of Suzhou,china,acquired on April 9,2009 and June 15,2010,are used for our experiment.The experimental results demonstrate that our method can reduce the false alarm rate effectively,as well as preserve a good change rate.Besides,the edge of changed objects are well preserved.

Key words:  SAR images;Super\      pixel segmentation;Fusion;Change detection     
Received:  03 April 2015      Published:  19 July 2016
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Zhang Mingzhe
Zhang Hong
Wang Chao
Liu Meng
Xie Lei

Cite this article: 

Zhang Mingzhe,Zhang Hong,Wang Chao,Liu Meng,Xie Lei. Combining Super\|pixel Segmentation and Multiple Difference Maps for SAR Change Detection. Remote Sensing Technology and Application, 2016, 31(3): 481-487.

URL: 

http://www.rsta.ac.cn/EN/10.11873/j.issn.1004-0323.2016.3.0481     OR     http://www.rsta.ac.cn/EN/Y2016/V31/I3/481

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