This paper proposes a new fully automated technique that can be used for the registration of medical images of the head. The method uses Chebyshev polynomials in order to approximate and then minimize a novel multiresolutional, signal intensity independent disparity function, which can generally be defined as the mean squared value of the mean weighted ratio of two images. This function is explicitly computed for n Chebyshev points in a geometric transformation parameter interval [-A, +A] transformation units and is approximated using the Chebyshev polynomials for all other points in the interval. For 3D T2-T1 weighted MR registration, 120 experiments with studies from ten patients were performed and showed that n = 4 Chebyshev points for A = 18 transformation units give mean rotational error 0.36 degrees and a mean translational error 0.36 mm. The different noise conditions did not affect the performance of the method. We conclude that the method is suitable for routine clinical applications and that it has significant potential for future development and improvement.