Automated Building Extraction from High-Resolution Satellite Imagery in Urban Areas Using Structural, Contextual, and Sp
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Automated Building Extraction from High-Resolution Satellite Imagery in Urban Areas Using Structural, Contextual, and Spectral Information Xiaoying Jin Department of Electrical and Computer Engineering, University of Missouri-Columbia, Columbia, MO 65211, USA Email: [email protected]
Curt H. Davis Department of Electrical and Computer Engineering, University of Missouri-Columbia, Columbia, MO 65211, USA Email: [email protected] Received 1 January 2004; Revised 17 August 2004 High-resolution satellite imagery provides an important new data source for building extraction. We demonstrate an integrated strategy for identifying buildings in 1-meter resolution satellite imagery of urban areas. Buildings are extracted using structural, contextual, and spectral information. First, a series of geodesic opening and closing operations are used to build a differential morphological profile (DMP) that provides image structural information. Building hypotheses are generated and verified through shape analysis applied to the DMP. Second, shadows are extracted using the DMP to provide reliable contextual information to hypothesize position and size of adjacent buildings. Seed building rectangles are verified and grown on a finely segmented image. Next, bright buildings are extracted using spectral information. The extraction results from the different information sources are combined after independent extraction. Performance evaluation of the building extraction on an urban test site using IKONOS satellite imagery of the City of Columbia, Missouri, is reported. With the combination of structural, contextual, and spectral information, 72.7% of the building areas are extracted with a quality percentage 58.8%. Keywords and phrases: building extraction, high-resolution satellite imagery, mathematical morphology, shadow, hypothesis and verification, information fusion.
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INTRODUCTION
Monocular building extraction has been an active research topic in photogrammetry and computer vision for many years. Some useful applications are automation in cartographic mapping and updating of geographic information system (GIS) databases. Early research on building extraction was often done using aerial imagery due to its high spatial resolution of 1 meter or less. A wide range of techniques and algorithms have been proposed for automatically constructing 2D or 3D building models from aerial imagery. Comprehensive surveys of research in this area can be found in [1, 2, 3]. Considering both radiometry and geometry, a large population of these algorithms are edge-based techniques [4, 5, 6] that consist of linear feature detection, grouping for parallelogram structure hypotheses extraction, and 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.
building polygons verification using knowledge such as geometric structure [5, 6], shadow [5, 7], illuminating angles [5], and so forth. In order
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