A noise-robust frequency domain technique for estimating planar roto-translations

This work presents a new method for estimating planar roto-translations that operates in the frequency domain and as such, is not based on features. Since the proposed technique uses all the image information, it is very robust against noise, it can be very accurate; estimation errors on the rotational angle varies from a few hundredths to a few tenths of a degree, depending on the noise level. Experimental evidence of this performance is presented, and the mathematical reasons behind these characteristics are explained in depth. Another remarkable feature of the algorithm consists in that it works in Cartesian coordinates, bypassing the need to transform from the Cartesian to the polar domain, which, typically, is a numerically delicate and computationally onerous task. The proposed technique can become an effective tool for unsupervised estimation of roto-translations by means of implementations based on FFT algorithms