High-accuracy sub-pixel motion estimation from noisy images in Fourier domain.

In this paper, we propose a new method for estimating sub-pixel motion via exploiting the principle of phase correlation in the Fourier domain. The method is based on linear weighting of the height of the main peak on the one hand and the difference between its two neighboring side-peaks on the other. Using both synthetic and real data we show that the proposed method outperforms many established approaches and achieves improved accuracy even in the presence of noisy samples.