This paper presents a concept for automated model-based image registration. The overall approach relies on computing a correspondence between a three-dimensional (1-D) data base and a reconnaissance image in terms of an appropriate sensor model as a function of such parameters as sensor location, orientation, scale, etc. The construction of such models is illustrated for frame camera and SAR sensors. Initial (platform ephemeris) parameter estimates are refined to achieve accurate correspondence by techniques which optimally match a collection of 3-D lineal features to an edge set extracted from the image. In the case of 3-D data bases consisting of stereo imagery (such as PPDBs) 3-D lineal features are automatically generated by applying the Marr-Poggio-Grimson computational models for stereo vision. The computed 3-D data-base-to-image correspondence can be used to predict accurately the image location of any 3-D point and to develop an elevation surface model associated with the image. This also leads to establishing automated model-based image-to-image registration.