SUI Haigang, CHEN Guang, HU Chuanwen, SONG Zhina. Integrated Segmentation, Registration and Extraction Method for Water-Body Using Optical Remote Sensing Images and GIS Data[J]. Geomatics and Information Science of Wuhan University, 2016, 41(9): 1145-1150. DOI: 10.13203/j.whugis20140460
Citation: SUI Haigang, CHEN Guang, HU Chuanwen, SONG Zhina. Integrated Segmentation, Registration and Extraction Method for Water-Body Using Optical Remote Sensing Images and GIS Data[J]. Geomatics and Information Science of Wuhan University, 2016, 41(9): 1145-1150. DOI: 10.13203/j.whugis20140460

Integrated Segmentation, Registration and Extraction Method for Water-Body Using Optical Remote Sensing Images and GIS Data

Funds: 

The National 973 Program of China 2012CB719906

the National 863 Program of China 2013AA122301

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  • Author Bio:

    SUI Haigang, PhD, professor, specializes in remote sensing image processing and information extraction, 3D GIS theory and application, integration and application of multi sensors information. E-mail: haigang_sui@263.net

  • Received Date: April 12, 2015
  • Published Date: September 04, 2016
  • Automatic water-body extraction from remote sensing images is a challenging problem. In this paper, a novel automatic water-body extraction technique is proposed for optical visible remote sensing images. It integrates image segmentation, image registration and change detection with GIS data as a whole process. A new iterative segmentation and registration strategy is also proposed. A multi-scale visual attention model is introduced to detect salient areas and a level-set segmentation algorithm is employed for image segmentation. An improved shape curve similarity (ISCS) method is presented to constrain the matching of image segmentation objects and GIS-identified water-bodies. Furthermore, a buffer-based change detection algorithm was designed to obtain unchanged water-bodies and non-water objects were eliminated with the aid of GIS data and spectral features. Experiments were carried out on three sets of data.Results show that the proposed method was effective in rapid water body extraction and change detection.
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