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Remote Sens. 2017, 9(5), 469;

An Automatic Shadow Detection Method for VHR Remote Sensing Orthoimagery

School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China
Research Center for Ocean Mapping and Applications, Shanghai Engineering Research Center of Hadal Science and Technology, College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China
Author to whom correspondence should be addressed.
Academic Editors: Richard Gloaguen and Prasad S. Thenkabail
Received: 8 February 2017 / Revised: 8 May 2017 / Accepted: 9 May 2017 / Published: 11 May 2017
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The application potential of very high resolution (VHR) remote sensing imagery has been boosted by recent developments in the data acquisition and processing ability of aerial photogrammetry. However, shadows in images contribute to problems such as incomplete spectral information, lower intensity brightness, and fuzzy boundaries, which seriously affect the efficiency of the image interpretation. In this paper, to address these issues, a simple and automatic method of shadow detection is presented. The proposed method combines the advantages of the property-based and geometric-based methods to automatically detect the shadowed areas in VHR imagery. A geometric model of the scene and the solar position are used to delineate the shadowed and non-shadowed areas in the VHR image. A matting method is then applied to the image to refine the shadow mask. Different types of shadowed aerial orthoimages were used to verify the effectiveness of the proposed shadow detection method, and the results were compared with the results obtained by two state-of-the-art methods. The overall accuracy of the proposed method on the three tests was around 90%, confirming the effectiveness and robustness of the new method for detecting fine shadows, without any human input. The proposed method also performs better in detecting shadows in areas with water than the other two methods. View Full-Text
Keywords: shadow detection; matting; VHR; DSM; geometrical method; skeleton operation shadow detection; matting; VHR; DSM; geometrical method; skeleton operation

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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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Wang, Q.; Yan, L.; Yuan, Q.; Ma, Z. An Automatic Shadow Detection Method for VHR Remote Sensing Orthoimagery. Remote Sens. 2017, 9, 469.

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