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Open AccessArticle

Land Surface Water Mapping Using Multi-Scale Level Sets and a Visual Saliency Model from SAR Images

by 1,†, 1,* and 2,†
1
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
2
National Disaster Reduction Center of China, NO.6 GuangBaiDongLu, Chaoyang District, Beijing 100124, China
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Academic Editors: Qiming Zhou, Zhilin Li and Wolfgang Kainz
ISPRS Int. J. Geo-Inf. 2016, 5(5), 58; https://doi.org/10.3390/ijgi5050058
Received: 5 January 2016 / Revised: 25 March 2016 / Accepted: 18 April 2016 / Published: 5 May 2016
(This article belongs to the Special Issue Advances and Innovations in Land Use/Cover Mapping)
Land surface water mapping is one of the most basic classification tasks to distinguish water bodies from dry land surfaces. In this paper, a water mapping method was proposed based on multi-scale level sets and a visual saliency model (MLSVS), to overcome the lack of an operational solution for automatically, rapidly and reliably extracting water from large-area and fine spatial resolution Synthetic Aperture Radar (SAR) images. This paper has two main contributions, as follows: (1) The method integrated the advantages of both level sets and the visual saliency model. First, the visual saliency map was applied to detect the suspected water regions (SWR), and then the level set method only needed to be applied to the SWR regions to accurately extract the water bodies, thereby yielding a simultaneous reduction in time cost and increase in accuracy; (2) In order to make the classical Itti model more suitable for extracting water in SAR imagery, an improved texture weighted with the Itti model (TW-Itti) is employed to detect those suspected water regions, which take into account texture features generated by the Gray Level Co-occurrence Matrix (GLCM) algorithm, Furthermore, a novel calculation method for center-surround differences was merged into this model. The proposed method was tested on both Radarsat-2 and TerraSAR-X images, and experiments demonstrated the effectiveness of the proposed method, the overall accuracy of water mapping is 98.48% and the Kappa coefficient is 0.856. View Full-Text
Keywords: water mapping; level sets; visual saliency model; SAR image water mapping; level sets; visual saliency model; SAR image
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Xu, C.; Sui, H.; Xu, F. Land Surface Water Mapping Using Multi-Scale Level Sets and a Visual Saliency Model from SAR Images. ISPRS Int. J. Geo-Inf. 2016, 5, 58.

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ISPRS Int. J. Geo-Inf., EISSN 2220-9964, Published by MDPI AG
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