Estimating Band-to-Band Misregistrations in Aliased Imagery

We compare two classes of techniques, cross-covariance-based and Fourier-based, for estimating band-to-band misregistrations in multispectral imagery. We show that both methods often give biased estimates of the misregistrations, the former because of inadequate interpolation procedures and the latter because they do not account for the presence of aliasing. Such aliasing is often present, especially in remote sensing imagery. We describe a Fourier-based method that accounts for aliasing and that, for a variety of 512 × 512 image pairs, gives misregistration estimates with standard errors quite often less than 1/100th of a pixel in both horizontal and vertical directions. The theory is applied to one artificial and three real image pairs, thus demonstrating some of its practical consequences. There is also a brief discussion of the implications of the theory for image registration.