Effective and robust motion estimation with sub-pixel accuracy is essential in many image processing and computer vision applications. Due to its computational efficiency and robustness in the presence of intensity changes as well as geometric distortions, phase correlation in the Fourier domain provides an attractive solution for global motion estimation and image registration. The paper aims to discuss these issues.
In this paper, relevant sub-pixel strategies are categorized into three classes, namely, single-side peak interpolation, dual-side peak interpolation and curve fitting. The well-known images “Barbara” and “Pentagon” were used to evaluate the performance of eight typical methods, in which Gaussian noise was attached in the synthetic data.
For eight such typical methods, the tests using synthetic data have suggested that considering dual-side peaks in interpolation or fitting helps to produce better results. In addition, dual-side interpolation outperforms curve fitting methods in dealing with noisy samples. Overall, Gaussian-based dual-side interpolation seems the best in the experiments.
Based on the comparisons of eight typical methods, the authors can have a better understanding of the phase correlation for motion estimation. The evaluation can provide useful guidance in this context.
The authors wish to acknowledge the financial support from Scientific Research Program funded by Shaanxi Provincial Education Department (Grant No. 15JK1310), the Natural Science Foundation of Shaanxi Province (Grant No. 2016JZ026), Control Science and Engineering Group Construction of Xi'an Polytechnic University (Grant No. 107090811), the National Natural Science Foundation of China (Grant No. 61672008), and the Natural Science Foundation of Guangdong Province (Grant No. 2016A030311013), and International Scientific and Technological Cooperation Projects of Education Department of Guangdong Province (Grant No. 2015KGJHZ021).
Ren, J., Zhao, H., Ren, J. and Cheng, S. (2016), "Sub-pixel motion estimation using phase correlation: comparisons and evaluations", International Journal of Intelligent Computing and Cybernetics, Vol. 9 No. 4, pp. 394-405. https://doi.org/10.1108/IJICC-03-2016-0009Download as .RIS
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