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The authors present a performance study of gradient correlation in the context of the estimation of interframe motion in video sequences. The method is based on the maximisation of the spatial gradient cross-correlation function, which is computed in the frequency domain and therefore can be implemented by fast transformation algorithms. Enhancements to the baseline gradient-correlation algorithm are presented which further improve performance, especially in the presence of noise. A comparative performance study is also presented, which demonstrates that the proposed method outperforms state-of-the-art methods 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.