Automatic geocoding of high value targets using structural image analysis and GIS data

Geocoding based merely on navigation data and sensor model is often not possible or precise enough. In these cases an improvement of the preregistration through image-based approaches is a solution. Due to the large amount of data in remote sensing automatic geocoding methods are necessary. For geocoding purposes appropriate tie points, which are present in image and map, have to be detected and matched. The tie points are base of the transformation function. Assigning the tie points is a combinatorial problem depending on the number of tie points. This number can be reduced using structural tie points like corners or crossings of prominent extended targets (e.g. harbors, airfields). Additionally the reliability of the tie points is improved. Our approach extracts structural tie points independently in the image and in the vector map by a model-based image analysis. The vector map is provided by a GIS using ATKIS data base. The model parameters are extracted from maps or collateral information of the scenario. The two sets of tie points are automatically matched with a Geometric Hashing algorithm. The algorithm was successfully applied to VIS, IR and SAR data.