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Remote Sens. 2015, 7(7), 8779-8802;

River Detection in Remotely Sensed Imagery Using Gabor Filtering and Path Opening

Department of Geographic Information Science, Nanjing University, Nanjing, Jiangsu 210023, China
Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing, Jiangsu 210023, China
Author to whom correspondence should be addressed.
Academic Editors: Deepak R. Mishra, Eurico J. D’Sa, Sachidananda Mishra and Prasad S. Thenkabail
Received: 12 May 2015 / Revised: 16 June 2015 / Accepted: 6 July 2015 / Published: 13 July 2015
(This article belongs to the Special Issue Remote Sensing of Water Resources)
Full-Text   |   PDF [6107 KB, uploaded 13 July 2015]   |  


Detecting rivers from remotely sensed imagery is an initial yet important step in space-based river studies. This paper proposes an automatic approach to enhance and detect complete river networks. The main contribution of this work is the characterization of rivers according to their Gaussian-like cross-sections and longitudinal continuity. A Gabor filter was first employed to enhance river cross-sections. Rivers are better discerned from the image background after filtering but they can be easily corrupted owing to significant gray variations along river courses. Path opening, a flexible morphological operator, was then used to lengthen the river channel continuity and suppress noise. Rivers were consistently discerned from the image background after these two-step processes. Finally, a global threshold was automatically determined and applied to create binary river masks. River networks of the Yukon Basin and the Greenland Ice Sheet were successfully detected in two Landsat 8 OLI panchromatic images using the proposed method, yielding a high accuracy (~97.79%), a high true positive rate (~94.33%), and a low false positive rate (~1.76%). Furthermore, experimental tests validated the high capability of the proposed method to preserve river network continuity. View Full-Text
Keywords: river detection; Gabor filter; path opening; Landsat 8 river detection; Gabor filter; path opening; Landsat 8

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Yang, K.; Li, M.; Liu, Y.; Cheng, L.; Huang, Q.; Chen, Y. River Detection in Remotely Sensed Imagery Using Gabor Filtering and Path Opening. Remote Sens. 2015, 7, 8779-8802.

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