A Frequency Domain Approach to Roto-translation Estimation using Gradient Cross-Correlation

A novel frequency domain approach to roto-translation estimation is presented. The baseline gradient cross-correlation method is extended to handle rotations. A key feature of the proposed scheme is the ability to achieve good performance in the presence of both large translations and rotations as well as noise, a scenario for which other Fourier-based methods typically fail. Robustness and accuracy in conjunction with computational efficiency, offered by the frequency domain formulation, make the algorithm useful in a number of image processing tasks such as image registration.