Motion estimation using hypercomplex correlation in the wavelet domain

We present a novel frequency-domain motion estimation technique, which employs hypercomplex correlation in the wavelet domain. Our method involves wavelet decomposition followed by cross-correlation in the frequency domain using the discrete quaternion Fourier transform. Experiments using both artificially induced motion and actual scene motion demonstrate that the proposed method outperforms the state-of-the-art in frequency-domain motion estimation, in the shape of phase correlation, in terms of sub-pixel accuracy for a range of test material and motion scenarios.