5 July 1995 Automated building height estimation and object extraction from multiresolution imagery
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Abstract
The built environment constitutes a very important target for automated image understanding systems. Currently, these environments only have manually surveyed 2D vector information in paper or digital map form. Increasingly, there are many requirements for 3D information. Automated systems are the only viable way to acquire this information over vast areas with a temporal frequency which will keep pace with the rate of change of many of these areas. Most published image understanding techniques for the automatic extraction of man-made objects only address a specific class of scene at a specific resolution. To address the full range of circumstances which will be required and make a technique more robust, it should be applied to multi-resolution images. In this paper, two automated systems one for building height extraction (stereoscopic) and one for building detection from monoscopic images are applied to multi-resolution aerial and spaceborne imagery. These systems were originally developed with for 0.15 m resolution inner city urban area imagery. With 0.24 m resolution suburban imagery, they performed very successfully. With 0.85 m resolution urban imagery containing very complicated buildings, they show promising results. A 2 m resolution Russian DD5 image was also tested with the monoscopic building detection system and the results showed automatic extraction of large industrial buildings is possible with such imagery. In summary, it was shown that these fully automated systems can handle images with various resolutions and environments.
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Taejung Kim, Taejung Kim, Jan-Peter A. Muller, Jan-Peter A. Muller, } "Automated building height estimation and object extraction from multiresolution imagery", Proc. SPIE 2486, Integrating Photogrammetric Techniques with Scene Analysis and Machine Vision II, (5 July 1995); doi: 10.1117/12.213126; https://doi.org/10.1117/12.213126
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