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Remote Sens. 2017, 9(3), 263; doi:10.3390/rs9030263

Automatic Detection of Low-Rise Gable-Roof Building from Single Submeter SAR Images Based on Local Multilevel Segmentation

1
Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
3
China Nanjing Research Institute of Electronics Technology, Nanjing 210039, China
*
Authors to whom correspondence should be addressed.
Academic Editors: Nicola Masini, Gonzalo Pajares Martinsanz and Prasad S. Thenkabail
Received: 4 November 2016 / Revised: 18 February 2017 / Accepted: 9 March 2017 / Published: 13 March 2017
View Full-Text   |   Download PDF [8134 KB, uploaded 15 March 2017]   |  

Abstract

Low-rise gable-roof buildings are a typical building type in shantytowns and rural areas of China. They exhibit fractured and complex features in synthetic aperture radar (SAR) images with submeter resolution. To automatically detect these buildings with their whole and accurate outlines in a single very high resolution (VHR) SAR image for mapping and monitoring with high accuracy, their dominant features, i.e., two adjacent parallelogram-like roof patches, are radiometrically and geometrically analyzed. Then, a method based on multilevel segmentation and multi-feature fusion is proposed. As the parallelogram-like patches usually exhibit long strip patterns, the building candidates are first located using long edge extraction. Then, a transition region (TR)-based multilevel segmentation with geometric and radiometric constraints is used to extract more accurate edge and roof patch features. Finally, individual buildings are identified based on the primitive combination and the local contrast. The effectiveness of the proposed approach is demonstrated by processing a complex 0.1 m resolution Chinese airborne SAR scene and a TerraSAR-X staring spotlight SAR scene with 0.23 m resolution in azimuth and 1.02 m resolution in range. Building roofs are extracted accurately and a detection rate of ~86% is achieved on a complex SAR scene. View Full-Text
Keywords: very high resolution (VHR); roof patch; roof ridge; parallelogram-like; transition region very high resolution (VHR); roof patch; roof ridge; parallelogram-like; transition region
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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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Chen, J.; Wang, C.; Zhang, H.; Wu, F.; Zhang, B.; Lei, W. Automatic Detection of Low-Rise Gable-Roof Building from Single Submeter SAR Images Based on Local Multilevel Segmentation. Remote Sens. 2017, 9, 263.

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