Automatic bridge detection in high-resolution satellite images

Authors:
Roger Trias-Sanz;Nicolas Loménie
Affiliations:
Université de Paris 5, Laboratoire SIP-CRIP5, Paris, France;Université de Paris 5, Laboratoire SIP-CRIP5, Paris, France
Venue:
ICVS'03 Proceedings of the 3rd international conference on Computer vision systems
Year:
2003

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Abstract

A set of methodologies and techniques for automatic detection of bridges in pan-chromatic, high-resolution satellite images is presented. These methods rely on (a) radiometric features and neural networks to classify each pixel into several terrain types, and (b) fixed rules to find bridges in this classification. They can be easily extended to other kinds of geographical objects, and integrated with existing techniques using geometric features. The proposed method has been tested in a number of experiments.