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A Method of Motion-Estimation-Based H.264 Video Coding Using Optimal Search-Range

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A Correction to this article was published on 12 February 2021

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Abstract

In multi-view video coding, inter-view and temporal redundancies decrease the coding efficiency and video quality, and they need to be eliminated. This paper proposes a method of motion-estimation-based H.264 video coding method using the optimal search-range for video broadcasting from a studio. In the method, first, a point-matching tool is used to match the corresponding points in the previous and current frames. These points are then calculated to obtain the movement vectors in order to estimate the corresponding points in the next frame, and the estimated corresponding points in the next frame are used as the centers for drawing circles, which are the individual search ranges. The corresponding points in the next frame are found in the determined search ranges by using the optical flow. They are finally encoded with the disparities and transmitted using the H.264 standard. To evaluate the performance of the proposed method, experiments with standard videos are performed, and the performance is approximately improved by 0.2–0.3 dB and 84 ms per 100 frames in terms of the PSNR (peak signal-to-noise ratio) and computational speed, respectively.

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References

  1. Smolic, A., & Kauff, P. (2005). Interactive 3-D video representation and coding technologies. Proceedings of IEEE, 93(1), 98–110.

    Article  Google Scholar 

  2. Smolic, A., Muller, K., Stefanoski, N., Ostermann, J., Gotchev, A., Akar, G., et al. (2007). Coding algorithms for 3DTVA survey. IEEE Transactions on Circuits and Systems for Video Technology, 17(11), 1606–1621.

    Article  Google Scholar 

  3. Ho, Y. S., & Oh, K. J. (2007). Overview of multi-view video coding. In 14th international workshop on signals and image processing systems (pp. 5–12).

  4. Liu, L., Zhu, F., Bosch, M., & Delp, E. J. (2007). Recent advances in video compression: What’s next? In: 9th international symposium on signal processing and its applications.

  5. Wiegand, T., Sullivan, J., Bjontegaard, G., & Luthra, A. (2003). Overerview of the H.264/AVC video coding standard. IEEE Transactions on Circuits and Systems for Video Technology.

  6. Sullivan, G. J., Topiwala, P., & Luthra, A. (2004). The H.264/AVC advanced video coding standard: overview and introduction to the fidelity range extensions. In SPIE conference on applications of digital image processing XXVII, Colorado, USA.

  7. Schwarz, H., Marpe, D., & Wiegand, T. (2006). Overview of the scalable H.264/MPEG4-AVC extension. In Proceedings of the IEEE international conference on image processing, Georgia, USA.

  8. Merkle, P., Muller, K., Smolic, A. & Wiegand, T. (2002). Efficient compression of multi-view video exploiting inter-view dependencies based on H.264/MPEG4-AVC. In IEEE International Conference on Multimedia and Expo (pp. 1717–1720).

  9. Tanimoto, M. (2008). FTV (Free viewpoint TV) and Creation of Ray-Based Image Engineering. ECTI Transaction on Electrical Engineering, Electronics and Communications, 6(1), 3–14.

    Google Scholar 

  10. Ohm, J. R. (2005). Advances in scalable video coding. Proceedings of the IEEE, 93(1), 42–56.

    Article  Google Scholar 

  11. Muller, K., Merkle, P., & Wiegand, T. (2007). Compressing time-varying visual content. IEEE Signal Processing Magazine, 24(6), 58–65.

    Article  Google Scholar 

  12. Iain, E. R. (2010). The H.264 advanced video compression standard. New York: Wiley.

    Google Scholar 

  13. Huang, Y. W., Chen, C.-Y., Tsai, C. H., Shen, C. F., & Chen, L. G. (2006). Survey on block matching motion estimation algorithms and architectures with new results. Journal of VLSI Signal Processing, Springer, 42(7), 297–320.

    Article  Google Scholar 

  14. Bovik, A. C. (2006). The essential guide to video processing. Atlanta: Elsevier. 978-0-12-374456-2.

  15. Li, R., Zeng, B., & Liou, M. L. (2002). A new three-step search algorithm for block motion estimation. IEEE Transactions on Circuits and Systems for Video Technology, 4(4), 438–442.

    Google Scholar 

  16. Po, L. M., & Ma, W. C. (1996). A novel four-step search algorithm for fast block motion estimation. IEEE Transactions Circuits System for Video Technology, 6(3), 313–317.

    Article  Google Scholar 

  17. Tham, J. Y., Ranganath, S., Ranganath, M., & Kassim, A. A. (1998). A novel unrestricted center-biased diamond search algorithm for block motion estimation. IEEE Transactions on Circuits and Systems for Video Technology, 8(4), 369–377.

    Article  Google Scholar 

  18. Zhu, S., & Ma, K. K. (2000). A new diamond search algorithm for fast block matching. IEEE Transactions on Circuits and Systems for Video Technology, 9(2), 287–290.

    Google Scholar 

  19. Liu, B., & Zaccartin, A. (1993). New fast algorithms for estimation of block motion vectors. IEEE Transactions on Circuits and Systems for Video Technology, 3(2), 148–157.

    Article  Google Scholar 

  20. Liu, L. K., & Feig, E. (1996). A block-based gradient descent search algorithm for block motion estimation in video coding. IEEE Transactions on Circuits and Systems for Video Technology, 6(4), 419–422.

    Article  Google Scholar 

  21. Song, X., Chiang, T., & Zhang, Y. Q. (1998). A scalable hierarchical motion estimation algorithm for MPEG-2. In IEEE international conference image process (ICIP) (pp. 126–129).

  22. Ghanbari, M. (2003). The cross-search algorithm for motion estimation. IEEE Transactions on Communication, 38(7), 950–953.

    Article  Google Scholar 

  23. Ismail, Y., McNeely, J. B., Shaaban, M., Mahmoud, H., & Bayoumi, M. A. (2012). Fast motion estimation system using dynamic models for H.264/AVC video coding. IEEE Transaction on Circuits and Systems for Video Technology, 22(1), 28–42.

    Article  Google Scholar 

  24. Boonthep, N., Chiracharit, W., Chamnongthai, K., & Higuchi, K. (2012). Improvement of disparity and motion estimation by geometry based for multiview video coding. In JICTEE conference.

  25. Boonthep, N., Chiracharit, W., & Chamnongthai, K. (2013). An efficient fractal based on variable block-size for multi-view video coding. In ECTI conference.

  26. Lowe, D. (2003). Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision, 20, 91–110.

    Google Scholar 

  27. Liu, K. H., Liu, T. J., & Liu, H. H. (2010). A SIFT descriptor based method for global disparity vector estimation in multiview video coding. In Multimedia and expo (ICME), IEEE international conference, 19–23 July 2010.

  28. Guo, J. M., Chang, L. Y., & Lee, J. D. (2019). An efficient and geometric-distortion-free binary robust local feature. Sensors, 19, 1–24.

    Article  Google Scholar 

  29. Lucas, B. D. (1984). Image matching by the method of differences. Pittsburgh: Carnegie Mellon University.

    Google Scholar 

  30. ISO/IEC MPEG & ITU-T VCEG. (2006). Common test condition for multiview video coding. JVT-U211.

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Acknowledgements

The financial support provided by the Thailand Research Fund through the Royal Golden Jubilee Ph.D. Program (Grant No. PHD/0144/2551), and the King Mongkut's University of Technology Thonburi are gratefully acknowledged.

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Authors and Affiliations

  1. Department of Electronic and Telecommunication Engineering, King Mongkut’s University of Technology Thonburi, Bangkok, Thailand

    Narasak Boonthep & Kosin Chamnongthai

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  1. Narasak Boonthep
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  2. Kosin Chamnongthai
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Correspondence to Kosin Chamnongthai.

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The original version of this article has been revised: The missing Acknowledgement section has been added.

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Boonthep, N., Chamnongthai, K. A Method of Motion-Estimation-Based H.264 Video Coding Using Optimal Search-Range. Wireless Pers Commun 115, 2833–2850 (2020). https://doi.org/10.1007/s11277-019-06766-4

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