Extraction and fusion of street networks from fine resolution SAR data

This paper deals with a feature fusion technique, especially implemented to characterize street networks extracted from multiple SAR images. The fusion approach may be useful in a number of ways: when applying different road extractors to the same data set, when using different pre-processing algorithms before applying the same road extractor to the same data set, or finally when applying the same road extractor to more images of the same area. The proposed approach applies "AND" and "OR" rules to the street nets to be compared. These operators are either hard or fuzzy ones, according to the way these networks were obtained. Therefore, the method is able to maintain the fuzzy reliability indicators obtained by fuzzy street extraction algorithms, but also to deal with differently classified segments and paths. We show through some examples how the proposed technique improves the results with respect to the "before fusion" street networks, and we also discuss future developments.