Abstract
With the urgent demand on urban synthetic aperture radar (SAR) image interpretation, this article deals with detecting buildings from a single high-resolution SAR image. Based on our previous work in building detection from SAR images, aiming at extracting buildings with their whole and accurate boundaries from the built-up area, a general framework using the marker-controlled watershed transform is introduced to combine both building characteristics and contextual information. First, the characteristics of the buildings and their surroundings are extracted as markers by the target detection techniques. Second, the edge strength image of the SAR image is computed using the ratio of exponentially weighted averages detector. The marker-controlled watershed transform is implemented with the markers and the edge strength image to segment buildings from the background. Finally, to remove false alarms, building features are considered. Especially, a shape analysis method, called direction correlation analysis, is designed to keep linear or L-shaped objects. We apply the proposed method to high-resolution SAR images of different scenes and the results validate that the new method is effective with high detection rate, low false-alarm rate, and good localization performance. Furthermore, comparison between the new method and our previous method reveals that introducing contextual information plays an important role in improve building detection performance.
Highlights
Synthetic Aperture Radar (SAR) is an active microwave sensor, making it capable of acquiring high-resolution imagery independent of daytime and weather conditions
The segmentation result of object B demonstrates that even a building in a SAR image is detected as several parts, it can be merge by our method as long as they are surrounded by correct external markers
Since the existing methods of building detection from SAR images are mostly not robust for images with complex scene or different appearances of buildings, a method of detecting buildings from a single high-resolution SAR images is proposed in this article, aiming at detecting buildings with their whole and accurate boundaries from the built-up area
Summary
Synthetic Aperture Radar (SAR) is an active microwave sensor, making it capable of acquiring high-resolution imagery independent of daytime and weather conditions. The marker-controlled watershed transform is often used to segment objects with some similarities (grey, texture, shape, etc), and quite suitable for extracting buildings in SAR images, which have distinct characteristics and strong similarities. In the built-up areas in SAR images, shadows and roads form black and netlike structures, which provide the main contextual information of buildings Such structures can be extracted and used as effective external markers. The segmentation result of object B demonstrates that even a building in a SAR image is detected as several parts, it can be merge by our method as long as they are surrounded by correct external markers (the shadow/road structure in this article). In [22], the DCA method was used in the stage of internal marker extraction to determine whether a region detected by the CFAR detector corresponds to a building or not. Since the Radon transform can efficiently be performed, the computational time can greatly be reduced
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
