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Improved Hybrid Block-Based Motion Estimation for Inter-frame Coding

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Abstract

Digital video technology has been increasingly needed in various fields, such as telecommunications, entertainment, medicine. Therefore, video compression is required. Motion estimation methods help in improving video compression efficiency by effectively removing the temporal redundancy between successive frames. Several block-based motion estimation (BME) algorithms are being suggested to reduce the coding process’s computational complexity. This paper proposes a new rapid hybrid (BME) algorithm established on the primary search point prediction and advance ending search point strategies. It combines rough adaptive search and effective local search. The coarse search introduces a new motion vector (MV) prediction technique that utilizes the macro-blocks (MBs) Spatio-temporal correlations to optimize the traditional adaptive-rood-pattern search algorithm (ARPS) and speeding up the whole process without affecting the accuracy. In the accurate local search, the cross-formed search pattern using a one-step search (OSS) block matching algorithm is employed, to estimate the actual (MV) with less computation time and further speed up the search efficiency. Exhaustive experiments are performed to demonstrate the present algorithm’s performance over the benchmark schemes concerning specific assessment criteria for results, including the peak signal-to-noise ratio (PSNR), computational complexity and computational gain. The results show that the proposed algorithm is efficient and reliable; it can always give better performance over diamond search (DS) and (ARPS). The conducted test shows an increased performance of search speed while preserving the visual quality of the motion-compensated images, and it achieves 59.76–88.03 speed improvement over (DS) and 20.98–72.06 over (ARPS) for different video sequences. Besides, the suggested method (ARP-OSS) provides the best result compared to (DS) and (ARPS) in terms of time complexity for analyzing all the video samples.

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Data Availability Statement

Data sharing not applicable to this article as no new datasets were generated or analyzed during the current study.

References

  1. I. Ahmad, W. Zheng, J. Luo, M. Liou, A fast adaptive motion estimation algorithm. IEEE Trans. Circuits Syst. Video Technol. 16(3), 420–438 (2006)

    Article  Google Scholar 

  2. A.F. Ahmadi, M.M. Azadfar, Implementation of fast motion estimation algorithms and comparison with full search method in h.264. Int. J. Comput. Sci. Netw. Secur. 8(3), 139–143 (2008)

    Google Scholar 

  3. S.M. Arora, K. Khanna, N. Rajpal, A novel hybrid approach for fast block based motion estimation. Int. J. Interact. Multimed. Artif. Intell. 4(6), 24–30 (2017)

    Google Scholar 

  4. S.P. Asare, A.V. Gokhale, C.M. Selukar, S.D. Kamble, Hybrid algorithm for block matching motion estimation technique, in 2015 International Conference on Communications and Signal Processing (ICCSP) (IEEE, 2015), pp. 1559–1563

  5. A. Barjatya, Block matching algorithms for motion estimation. IEEE Trans. Evol. Comput. 8, 225–239 (2004)

    Article  Google Scholar 

  6. S. Behera, D.P. Dogra, M.K. Bandyopadhyay, P.P. Roy, Estimation of linear motion in dense crowd videos using langevin model. Expert Syst. Appl. 150, 113333 (2020)

    Article  Google Scholar 

  7. B. Dash, S. Rup, F. Mohant, M.N. Swamy, A hybrid block-based motion estimation algorithm using jaya for video coding techniques. Digit. Signal Proc. 88, 160–171 (2019)

    Article  Google Scholar 

  8. M. Ghoneim, A. Hagag, J. Lu, T. Yahagi, A very fast and efficient search algorithm for block motion estimation. J. Signal Process 11(1), 69–74 (2007)

    Google Scholar 

  9. Y. Ismail, M.A. Elgamel, M.A. Bayoumi, Fast variable padding motion estimation using smart zero motion prejudgment technique for pixel and frequency domains. IEEE Trans. Circuits Syst. Video Technol. 19(5), 609–626 (2009)

    Article  Google Scholar 

  10. D.J. Jayaswal, M.A. Zaveri, Efficient hybrid search for motion estimation. SPIT- IEEE Colloq. Int. Conf. 1, 146–151 (2008)

    Google Scholar 

  11. B. Kim, S. Song, P. Mah, Enhanced block motion estimation based on distortion-directional search patterns. Pattern Recognit. Lett. 27, 1325–1335 (2006)

    Article  Google Scholar 

  12. J. Kim, B. Kim, C. Cho. Distortion-based partial distortion search for fast motion estimation (2007)

  13. J. Kim, B. Kim, S. Song, C. Cho, A directional and adaptive diamond search by adaptive pattern switching with a predicted motion vector, in 2006 International Conference on Image Processing (2006), pp. 2357–2360

  14. T. Koga, K. Iinuma, A. Hirano, Y. Iijima, T. Ishiguru, Motion compensated interframe coding for video-conferencing, in Proceedings of the National Telecommunications Conference (1981), pp. G5–3

  15. S.K. Kumaran, S. Mohapatra, D.P. Dogra, P.P. Roy, B. Kim, Computer vision-guided intelligent traffic signaling for isolated intersections. Expert Syst. Appl. 134, 267–278 (2019)

    Article  Google Scholar 

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

    Article  Google Scholar 

  17. M.L. Lin, Q.M. Yi, M. Shi, A fast and adaptive search algorithm based on rood pattern and gradient descent. Phys. Procedia 33, 1526–1532 (2012)

    Article  Google Scholar 

  18. J. Luo, X. Yang, L. Liu, A fast motion estimation algorithm based on adaptive pattern and search priority. Multimed. Tools Appl. 74, 11821–11836 (2014)

    Article  Google Scholar 

  19. A. Mathur, R. Bhandari, A. Mishra, An Improved Block-Based Motion Estimation Algorithm for Compressing a Video (Springer, Berlin, 2019), pp. 207–212

    Google Scholar 

  20. A. Moradi, R. Dianat, S. Kasaei, M. Taghi, M. Shalmani, Enhanced cross-diamond-hexagonal search algorithms for fast block motion estimation, in IEEE Conference on Advanced Video and Signal Based Surveillance (IEEE, 2005), pp. 558–563

  21. S. Mukherjee, R. Saini, P. Kumar, P.P. Roy, D.P. Dogra, B. Kim, Fight detection in hockey videos using deep network. J. Multimed. Inf. Syst. 4(4), 225–232 (2017)

    Google Scholar 

  22. Y. Nie, K.K. Ma, Adaptive rood pattern search for fast block-matching motion estimation. IEEE Trans. Image Process. 11(12), 1442–1449 (2002)

    Article  Google Scholar 

  23. L. Po, W. Ma, 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 

  24. V. Rajamanickam, S. Marikkannan, T. Rajavelu, An hybrid motion estimation algorithm for video coding standards. Int. J. Appl. Eng. Res. 10, 4885–4894 (2015)

    Google Scholar 

  25. M.A. Rawoof, D.L. Reddy, A.V. Paramkusam, R.V. Krishnaiah, A fast search block-based motion estimation algorithm for compression of motion pictures. Int. J. Mech. Eng. Technol. 8, 662–675 (2017)

    Google Scholar 

  26. T. Sebastian, J. Anitha, Hybrid hierarchical search motion estimation for video compression, in 2016 2nd International Conference on Advances in Electrical, Electronics, Information, Communication and Bio-Informatics (AEEICB) (IEEE, 2016), pp. 88–92

  27. C.M. Wu, J.Y. Huang, A new block matching algorithm for motion estimation. Appl. Mech. Mater. 855, 178–183 (2017)

    Article  Google Scholar 

  28. R. Yaakob, A. Aryanfar, A.A. Halin, N. Sulaiman, A comparison of different block matching algorithms for motion estimation. Procedia Technol. 11, 199–205 (2013)

    Article  Google Scholar 

  29. Y. Yan, S. Meng, A new hybrid search scheme for video motion estimation. J. Converg. Inf. Technol. 6(3), 106–112 (2011)

    Google Scholar 

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

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Computer Science, University of Sulaimani, Sulaimani Polytechnic University, KRG, Sulaymaniyah, Iraq

    Yusra Ahmed Salih

  2. Department of Remote Sensing and GIS, Baghdad University, Baghdad, Iraq

    Loay Edwar George

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  1. Yusra Ahmed Salih
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  2. Loay Edwar George
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Correspondence to Yusra Ahmed Salih.

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Salih, Y.A., George, L.E. Improved Hybrid Block-Based Motion Estimation for Inter-frame Coding. Circuits Syst Signal Process 40, 3500–3522 (2021). https://doi.org/10.1007/s00034-020-01637-x

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