Skip to main content
Log in

Adjustable SAD matching algorithm using frequency domain

  • Original Research Paper
  • Published:
Journal of Real-Time Image Processing Aims and scope Submit manuscript

Abstract

Fast Fourier transforms (FFTs) which are O(N logN) algorithms to compute a discrete Fourier transform (DFT) of size N have been called one of the ten most important algorithms of the twentieth century. However, even though many algorithms have been developed to speed up the computation the sum of absolute difference (SAD) matching, they are exclusively designed in the spatial domain. In this paper, we propose a fast frequency algorithm to speed up the process of (SAD) matching. We use a new approach to approximate the SAD metric by cosine series which can be expressed in correlation terms. These latter can be computed using FFT algorithms. Experimental results demonstrate the effectiveness of our method when using only the first correlation terms for block and template matching in terms of accuracy and speed. The proposed algorithm is suitable for software implementations and has a deterministic execution time unlike the existing fast algorithms for SAD matching.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Chen, J.J.F., Duluk, C.-K.: System and method for cross correlation with application to video MV estimator. No. US Patent 5,535,288, July 1996 (online). Available: http://www.freepatentsonline.com/5535288.html (1996)

  2. Essannouni, F., Thami, R.O.H., Salam, A., Aboutajdine, D.: A new fast full search block matching algorithm using frequency domain. In: IEEE ISSPA. Sydeny, vol. 2, pp. 559–562 (2005)

  3. Kilthau, S.D., Moller, T.M.S.: Full search content independent block matching based on the fast fourier transform. In: ICIP, pp I-669– I-672 (2002)

  4. Frigo, M., Johnson, S.G.: FFTW: an adaptive software architecture for the FFT. In: Proc. IEEE Intl. Conf. on Acoustics, Speech, and Signal Processing. Seattle, vol. 3, pp. 1381–1384 (online). Available: http://www.fftw.org/ (1998)

  5. Cooley, J.W., Tukey, J.W.: An algorithm for the machine calculation of complex Fourier series. Math. Comput. 19, 297–301 (1965)

    Article  MATH  Google Scholar 

  6. Sebe, N., Lew, M.S., Huijsmans, D.P.: Toward improved ranking metrics. IEEE Trans. Pattern Anal. Mach. Intell. 22(10), (2000)

  7. Koga, T., Iinuma, K., Hirano, A., Iijima, Y.: Motion compensated interframe coding for video conferencing. In: NTC’ 81 Conference Record, pp. G5.3.1–G5.3.5 (1981)

  8. Li, R., Zeng, B., Liou, M.: A new three-step search algorithm for block motion estimation. IEEE Trans. Circuits Syst. Video Technol. 4(4), 438–442 (1994)

    Article  Google Scholar 

  9. Lu, J., Liou, M.: A simple and efficient search algorithm for block-matching motion estimation. IEEE Trans. Circuits Syst. Video Technol. 7(2), 429–433 (1997)

    Article  Google Scholar 

  10. Po, L., Ma, W.: A novel four-step search algorithm for fast block motion estimation. IEEE Trans. Circuits Syst. Video Technol. 6(3), 313–317 (1996)

    Article  Google Scholar 

  11. Zhu, S., Ma, K.: A new diamond search algorithm for fast block-matching motion estimation. IEEE Trans. Image Process. 9(2), 287–290 (2000)

    Article  Google Scholar 

  12. Li, W., Salari, E.: Successive elimination algorithm for motion estimation. IEEE Trans. Image Process. 4(1), 105–107 (1995)

    Article  Google Scholar 

  13. Lin, Y., Tai, S.: Fast full-search block-matching algorithm for motion-compensated video compression. IEEE Trans. Commun. 45(5), 527–531 (1997)

    Article  Google Scholar 

  14. Chen, Y., Hung, Y., Fuh, C.: Fast block matching algorithm based on the winner-update strategy. IEEE Trans. Image Process. 10(8), 1212–1222 (2001)

    Article  MATH  Google Scholar 

  15. Ahn, T., Moon, Y., Kim, J.: An improved multilevel successive elimination algorithm for fast full-search motion estimation. In: ICIP03, vol. II, pp. 351–354 (2003)

  16. Fitch, A., Kadyrov, A., Christmas, W., Kittler, J.: Fast robust correlation. IEEE Trans. Image Process. 14(8), 1063–1073 (2005)

    Article  Google Scholar 

  17. Essannouni, F., Thami, R.O.H., Salam, A., Aboutajdine, D.: An optimal and statistically robust correlation technique for block based motion estimation. In: IEEE ICME 2006, Toronto, pp. 233–236 (2006)

  18. Di Stefano, L., Marchionni, M., Mattoccia, S.: A fast area-based stereo matching algorithm. Image Vis. Comp. 22(12), 983–1005 (2004)

    Article  Google Scholar 

  19. Kim, J.C., Lee, K.M., Choi, B.T., Lee, S.U.: A dense stereo matching using two-pass dynamic programming with generalized ground control points. In: CVPR ’05: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’05), Vol. 2, pp. 1075–1082. IEEE Computer Society, Washington (2005)

  20. Frigo, M., Johnson, S.G.: The design and implementation of FFTW3. Proceedings of the IEEE, vol. 93(2), pp. 216–231, special issue on Program Generation, Optimization, and Platform Adaptation (2005)

  21. Yang, L., Zhang, K., Liu, H., Huang, J., Huang, S.: An efficient locally pipelined FFT processor. IEEE Trans. Circuits Syst. II: Express Briefs 53(7), 585–589 (2006)

    Article  Google Scholar 

  22. Arfken, G.B.: Mathematical Methods for Physicists, 3rd edn. Academic, Orlando (1985)

  23. Churchill, R.V.: Fourier Series and Boundary Value Problems, 5th edn. McGraw-Hill, New York (1993)

    Google Scholar 

  24. Sorenson, H.V., Heideman, M.T., Burrus, C.S.: On computing the split-radix FFT. IEEE Trans. Acoust. Speech Signal Process. 34, 152–156 (1986)

    Article  Google Scholar 

  25. Johnson, S.G., Frigo, M.: A modified split-radix FFT with fewer arithmetic operations. IEEE Trans. Signal Process. 55(1), 111–119 (2007)

    Article  Google Scholar 

  26. Frigo, M., Johnson, S.G.: The FFTW web page (online). Available: http://www.fftw.org/ (2006)

Download references

Acknowledgments

Special thanks to Radouan Faizi from Mohammed V University -Souissi- ENSIAS for proofreading and also to Steven G. Johnson from the faculty of Applied Mathematics (MIT) for helpful conversations. This work has been supported by Maroc Telecom (Emotion project).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to F. Essannouni.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Essannouni, F., Thami, R.O.H., Aboutajdine, D. et al. Adjustable SAD matching algorithm using frequency domain. J Real-Time Image Proc 1, 257–265 (2007). https://doi.org/10.1007/s11554-007-0026-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11554-007-0026-0

Keywords

Navigation