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. © Springer-Verlag Berlin Heidelberg 2003.
CITATION STYLE
Trias-Sanz, R., & Loménie, N. (2003). Automatic bridge detection in high-resolution satellite images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2626, pp. 172–181). Springer Verlag. https://doi.org/10.1007/3-540-36592-3_17
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