Research Papers

Automatic change detection in remote sensing images using level set method with neighborhood constraints

[+] Author Affiliations
Guo Cao

Nanjing University of Science and Technology, The School of Computer Science and Technology, Nanjing 210094, China

Yazhou Liu

Nanjing University of Science and Technology, The School of Computer Science and Technology, Nanjing 210094, China

Yanfeng Shang

The Third Research Institute of Ministry of Public Security, Shanghai 201204, China

J. Appl. Remote Sens. 8(1), 083678 (Feb 14, 2014). doi:10.1117/1.JRS.8.083678
History: Received July 3, 2013; Revised January 2, 2014; Accepted January 13, 2014
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Abstract.  An automatic change detection (CD) method based on level set evolution in remote sensing images is proposed. The CD problem is formulated as a segmentation issue to discriminate the changed class from the unchanged class in the difference images. The strategy of the level set initialization is considered and neighborhood constraints are added to the level set energy model. In addition, a coarse-to-fine procedure is adopted. A chief advantage of our approach is to be able to obtain correct results even when the difference image contains different types of changes. Furthermore, the proposed method is robust against noise and yields smooth boundaries of changed regions without manual parameter adjustment. We implement the proposed method in a multiresolution framework and validate the algorithm systematically with a variety of remote sensing images by low- as well as high-spatial resolution sensors, including Landsat-5 TM, SPOT5, IKONOS, etc.

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© 2014 Society of Photo-Optical Instrumentation Engineers

Citation

Guo Cao ; Yazhou Liu and Yanfeng Shang
"Automatic change detection in remote sensing images using level set method with neighborhood constraints", J. Appl. Remote Sens. 8(1), 083678 (Feb 14, 2014). ; http://dx.doi.org/10.1117/1.JRS.8.083678


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