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A simple but effective bias reduction technique is developed based on the anti-symmetric feature of the sub-pixel image registration bias. Depending on the error propagation theory, the anti-symmetric feature is mathematically derived through a classical subset-based digital image correlation algorithm considering the most common error sources i.e. the grey-intensity interpolation scheme and random noise. This leads to the sub-pixel registration bias formulated in the form of an analytic expression that consists of the interpolation-induced phase error and the random noise induced bias, which is also further illustrated by numerical simulations. Bias reduction is achieved by compensating the bias at a certain sub-pixel displacement with the bias at the corresponding anti-symmetric sub-pixel displacement where the Fourier shift theorem is employed to alter the displacement without introducing extra bias. The performance of proposed method is validated using numerical case studies with different interpolation schemes and noise levels, by which the sub-pixel registration bias is shown to be significantly reduced.