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Given two images of roughly the same scene, image registration is the process of determining the transformation that most nearly maps one image to another. This problem is of particular interest in remote sensing applications, where it is known that two images correspond to roughly the same gecgraphic region, but the exact alignment between the images io not known. There are many approaches to image registration. We will consider an approach based on extracting a Ret of point features from each of the two images, and thus reducing the problem to a point pattern matching problem. Because of measurement errors and the presence of outlying data points in either of the images, it is important that the diotance measure between two point sets be robust to theeo cffecto. We will measure distances using the partial Hauodorff distance, An important element of image registration applications is that the search begins with a priori information on the bounds of transformation, and a good algorithm should be able to take advantage of this information. Point matching can be a computationally intensive task, and there have been a number of algorithms and approaches proposed for solving this problem, both from theoretical and applied standpoints. One common approach is based on a

Improved algorithms for robust point pattern matching and applications to image registration