Iterative Gradient-Based Shift Estimation: To Multiscale or Not to Multiscale?

Fast global shift estimation is a critical preprocessing step on many high level tasks such as remote sensing or medical imaging. In this work we deal with a simple question: should we use an iterative technique to perform shift estimation or should we use a multiscale approach. Based on the obtained results, both methodologies proved to lose accuracy as the noise increases, however this accuracy loss increases with the shift magnitude. The conclusion is that a multiscale strategy should be used when the shift magnitude is higher than approximately a fifth of a pixel.