Open Access

Automated Building Extraction from High-Resolution Satellite Imagery in Urban Areas Using Structural, Contextual, and Spectral Information

EURASIP Journal on Advances in Signal Processing20052005:745309

https://doi.org/10.1155/ASP.2005.2196

Received: 1 January 2004

Published: 25 August 2005

Abstract

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, of the building areas are extracted with a quality percentage .

Keywords and phrases

building extraction high-resolution satellite imagery mathematical morphology shadow hypothesis and verification information fusion

Authors’ Affiliations

(1)
Department of Electrical and Computer Engineering, University of Missouri-Columbia

Copyright

© X. Jin and C. H. Davis 2005

This article is published under license to BioMed Central Ltd. 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.