A method of image registration is presented for the case when the deformation between two images can be well approximated with a combination of translation, rotation, and global scaling. The method achieves very high accuracy by combining a global optimization in the 4- dimensional discrete parameter space with a local optimization in the 4-dimensional continuous parameter space. The 4-dimensional global optimization is accomplished with two 2- dimensional optimizations. The Fourier magnitude is used to decouple translation from rotation and scaling, and a log-polar mapping of the Fourier magnitude is used to convert rotation and scaling into shifts. Optimal rotation and scaling parameters are determined with a cross-correlation in the log-polar domain. After compensation for rotation and scaling differences, cross-correlation in the spatial domain yields the translation parameters. The four registration parameters are further refined with a local optimization using the correlation coefficient as a similarity measure in the 4-dimensional continuous parameter space. Results are shown from simulations and from registration of retinal images. For simulated images with a signal-to-noise ratio of -5 dB, the accuracy of the registration method is estimated to be better than 0.07 degrees, 0.1%, and 0.3 pixels for rotation, scaling, and translation, respectively. In the case of 512 X 512 pixel images the computation resource requirements are compatible with high end PCs, i.e., approximately 25 minutes on an Intel 80486/33 MHz based IBM/PC compatible.