Automatic control-point selection for image registration using disparity fitting

We present an algorithm for automatically selecting and matching control points for the purpose of registering images acquired using different imaging modalities. The modulus maxima of the wavelet transform were used to define a criterion for identifying control points. This criterion is capable of selecting points based on the size of features in the image. This technique can be tailored, by adjusting the scale of the filters in the modulus calculation, to the specific objects or structures known to occur in each image being registered. The control-point matching technique includes an iterative method for reducing the set of control-point pairs using the horizontal and vertical disparities between the matched pairs of points. Least-squares planes are fit to the horizontal and vertical disparity data, and control-point pairings are deleted based on their distances from those planes. The remaining points are used to recompute the planes. The process is iterated until the remaining points fall within a certain distance from the planes. Finally, a spatial transformation is performed on the template image to bring it into alignment with the reference image. The result of the control-point pair reduction is a more accurate alignment than what would have been produced using the initial control-point pairs. These techniques are applicable to medical images, but examples are given using images of paintings.