Combining data from different sensors of the same scene acquired at different times to create a hybrid is a common task in remote sensing. The first step of this task is to register these same-scene images (geometric integration). The accuracy of this step is important to create a valuable final hybrid image. The second step is radiometric integration (data fusion), which enriches the information of individual pixels in the image. This paper addresses the first task, i.e. geometric integration, and introduces a new method for automatically registering two dissimilar images, such as a radar image and an optical image, with high accuracy. Pre-registration of the two images is required to within a specified tolerance, which in our examples is up to 15 pixels at the higher resolution image and may be achieved by, for example, visually-located control points. The proposed approach then uses large-scale edge gradient contours in a process that automatically locates candidate control points on the contours. The points are selected using a cost function that involves the degree of match between all possible pairs of points. Numerous control points (around 50 pairs are typical) are found from matched pairs of gradient contours and used in a global, rubber sheet polynomial warp to refine the registration. This approach is applied to register a Synthetic Aperture Radar (SAR) image (ERS2, 12.5m pixels) and a Thematic Mapper (TM) image (Landsat5, 28.5m pixels) automatically. An example is shown and discussed in terms of residual registration error and processing efficiency.