Highly Accurate Estimation of Sub-pixel Motion Using Phase Correlation

  • Yinghuai Yu
  • Jinrong Wang
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 321)


Motion estimation is one of the basic problems in digital video processing; it is significant in the applications of video image compression, super-resolution reconstruction, mosaic, and target detection, and so on. In the base of discussing usual phase correlation algorithm, we present an improved algorithm for the problem of highly accurate sub-pixel motion estimation, which introduces zero-padding for computing the initial estimate at sub-pixel level, and also adopts the method of paraboloid fitting phase correlation for refining the initial estimate. Experimental results show that the proposed algorithm can not only achieve good robustness to the influence of noise, but can also improve the accuracy of motion estimation significantly.


Sub-pixel motion estimation phase correlation zero-padding paraboloid fitting 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Oguri, T., Ikehara, M., Nguyen, T.: 3D CUBE Video Coding Using Phase Correlation Motion Estimation. Electronics and Communications in Japan (Part III: Fundamental Electronic Science) 89(5), 32–38 (2006)CrossRefGoogle Scholar
  2. 2.
    Montoliu, R., Pla, F.: Accurate image registration by combining feature-based matching and GLS-Based motion estimation. In: 2nd International Conference on Computer Vision Theory and Applications, pp. 386–389. INSTICC Press, Barcelona (2007)Google Scholar
  3. 3.
    Barceló, L., Felip, L.R., Binefa, X.: A new approach for real time motion estimation using robust statistics and mpeg domain applied to mosaic images construction. In: IEEE International Conference on Multimedia and Expo, pp. 398–401. IEEE Computer Society Press, Amsterdam (2005)CrossRefGoogle Scholar
  4. 4.
    Li, Z.L., Xu, C., Li, Y.: Robust object tracking using mean shift and fast motion estimation. In: 2007 International Symposium on Intelligent Signal Processing and Communications Systems, pp. 734–737. IEEE Inc. Press, Xiamen (2008)Google Scholar
  5. 5.
    Guizar-Sicairos, M., Thurman, S.T., Fienup, J.R.: Efficient subpixel image registration algorithms. Optics Letters 33(2), 156–158 (2008)CrossRefGoogle Scholar
  6. 6.
    Kuglin, C.D., Hines, D.C.: The phase correlation image alignment method. In: IEEE International Conference on Cybernetics and Society, vol. 1, pp. 163–165. IEEE Press, New York (1975)Google Scholar
  7. 7.
    Argyriou, V., Vlachos, T.: Extrapolation-free arbitrary-shape motion estimation using phase correlation. Journal of Electronic Imaging 15(1), 0105011–0105013 (2006)CrossRefGoogle Scholar
  8. 8.
    Zhao, D.P., Wang, Y.J.: Application of Phase Correlation in the Spacial Object Orientation Based on SVD. Journal of Image and Graphics 12(1), 98–103 (2007)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Yinghuai Yu
    • 1
    • 2
  • Jinrong Wang
    • 3
  1. 1.College of InformationGuangdong Ocean UniversityZhanjiangChina
  2. 2.Lab of Ocean Remote Sensing & Information TechnologyGuangdong Ocean UniversityZhanjiangChina
  3. 3.College of ScienceGuizhou UniversityGuiyangChina

Personalised recommendations