This paper discusses a new method for the automatic matching of ground control points (GCPs) between satellite remote
sensing Image and digital raster graphic (DRG) in urban areas. The key of this method is to automatically extract tie
point pairs according to geographic characters from such heterogeneous images. Since there are big differences between
such heterogeneous images respect to texture and corner features, more detail analyzations are performed to find
similarities and differences between high resolution remote sensing Image and (DRG). Furthermore a new algorithms
based on the fuzzy-c means (FCM) method is proposed to extract linear feature in remote sensing Image. Based on linear
feature, crossings and corners extracted from these features are chosen as GCPs. On the other hand, similar method was
used to find same features from DRGs. Finally, Hausdorff Distance was adopted to pick matching GCPs from above two
GCP groups. Experiences shown the method can extract GCPs from such images with a reasonable RMS error.
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