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28 September 2009 An advanced technique for building detection in VHR SAR images
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The new spaceborne very high resolution (VHR) synthetic aperture radar (SAR) sensors, such as TerraSAR-X and Cosmo-SkyMed permit to extract information from VHR SAR data in urban areas at the level of individual buildings. To support the widespread usage of VHR SAR for different application scenarios (e.g. damage assessment after natural disasters), and hence to increase the value of the data, automatic methods for building detection and reconstruction should be developed. In this paper we present a novel method for automatic building detection from single detected VHR SAR imagery. In a first step we extract basic features (e.g. lines) and identify their semantic meaning modeled as the degree of membership of the feature to a certain scattering class (e.g. double bounce). Then, we analyze the features extracted in a neighborhood system to identify building candidates using a production system. Finally, a score is calculated for each building candidate based on the semantic meaning of its features. This score is used to select or reject a candidate for the final set of extracted buildings. The preliminary results obtained on single detected VHR SAR images of an urban area show that the method effectively detects flat and gable roof buildings with only few missed and almost no false alarms.
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Adamo Ferro, Dominik Brunner, and Lorenzo Bruzzone "An advanced technique for building detection in VHR SAR images", Proc. SPIE 7477, Image and Signal Processing for Remote Sensing XV, 74770V (28 September 2009);


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