Image registration in electron microscopy: application of a robust method

The geometric registration of two electron microscopic images generally is performed by maximizing the cross-correlation coefficient between them. We show that a new similarity measure (the number of sign changes) is useful for performing simultaneously geometric and gray-level registration. This method is robust, which means that it provides a good estimation of the parameters even in the presence of outliers that cannot be described by the registration model.