Analog Integrated Circuits and Signal Processing

, Volume 73, Issue 3, pp 931–944

Hardware design focusing in the tradeoff cost versus quality for the H.264/AVC fractional motion estimation targeting high definition videos

  • Gustavo Sanchez
  • Marcel Corrêa
  • Diego Noble
  • Marcelo Porto
  • Sergio Bampi
  • Luciano Agostini
Article

Abstract

This article presents an architecture for the fractional motion estimation (FME) of the H.264/AVC video coding standard focusing in a good tradeoff between the hardware cost and the video quality. The support to FME guarantees a high quality in the motion estimation process. The applied algorithmic simplifications together with the multiplierless implementation and with a well balanced pipeline allow a low cost and a high throughput solution. The architecture was also designed to avoid redundant external memory accesses when computing the FME. The design was divided in two main modules: integer motion estimation (with diamond search algorithm) and fractional refinement (half-pixel and quarter-pixel interpolation and search). The designed architecture was described in VHDL and synthesized to an Altera Stratix III FPGA. The architecture is able to reach 260 MHz when running in the target FPGA. In worst case scenario, this operation frequency allows a processing rate of 43 HD 1080p (1,920 × 1,080 pixels) frames per second, surpassing the requirements for real time processing. In comparison to related works, the developed architecture was able to achieve a good tradeoff among hardware costs, video quality and processing rate.

Keywords

Video coding H.264/AVC standard Motion estimation FPGA based design 

References

  1. 1.
    ITU-T e ISO/IEC JTC1. (1994). Generic coding of moving pictures and associated audio information—Part 2: video. ITU-T Rec. H.262 and ISO/IEC 13818–2 (MPEG-2).Google Scholar
  2. 2.
    Vanne, J., Aho, E., Kuusilinna, K., & Hämäläinen, T. (2009). A configurable motion estimation architecture for block-matching algorithms. New York: IEEE Transactions on Circuits and Systems for Video Technology.Google Scholar
  3. 3.
    Alencar, M. (2009). Digital television systems. Cambridge: Cambridge University Press.Google Scholar
  4. 4.
    JCT. (2011). Working draft 3 of high-efficiency video coding. JCTVC-E603.Google Scholar
  5. 5.
    Richardson, I. (2003). H.264 and MPEG-4 video compression–video coding for next-generation multimedia. Chichester: Wiley.CrossRefGoogle Scholar
  6. 6.
    Bhaskaran, V., & Konstantinides, K. (1999). Image and video compression standards: algorithms and architectures (2nd ed.). Boston: Kluwer Academic Publishers.Google Scholar
  7. 7.
    Tham, J., Ranganath, S., Ranganath, M., & Kassim, A. (1998). A novel unrestricted center-biased diamond search algorithm for block motion estimation. New York: IEEE Transactions on Circuits and Systems for Video Technology.Google Scholar
  8. 8.
    Corrêa, M., Schoenknecht, M., Dornelles, R., & Agostini, L. (2011). A high-throughput hardware architecture for the H.264/AVC half-pixel motion estimation targeting high-definition videos. International Journal of Reconfigurable Computing, 2011. doi:10.1155/2011/254730.
  9. 9.
    Choi, W., Jeon, B., & Jeong, J. (2003). Fast motion estimation with modified diamond search for variable motion block sizes. International Conference on Image Processing.Google Scholar
  10. 10.
    Xiph.org: test media. Retrieved October, 2011, from http://media.xiph.org/video/derf/.
  11. 11.
    JM 18. (2011). H.264/AVC JM reference software. http://iphome.hhi.de/suehring/tml.
  12. 12.
    Porto, M., Silva, A., Almeida, S., Costa, E., & Bampi, S. (2010). Motion estimation architecture using efficient adder-compressors for HDTV video coding. Journal of Integrated Circuits and Systems, 5, 78–88.Google Scholar
  13. 13.
    Kthiri, M., Loukil, H., Werda, I., Ben Atitallah, A., Samet, A., & Masmoudi, N. (2009). Hardware implementation of fast block matching algorithm in FGPA for H.264/AVC. International Multi-Conference on Systems, Signals & Devices.Google Scholar
  14. 14.
    Tasdizen, O., et al. (2009). Dynamically variable step search motion estimation algorithm and a dynamically reconfigurable hardware for its implementation. IEEE Transactions on Consumer Electronics, 55(3), 1645–1653.CrossRefGoogle Scholar
  15. 15.
    Kao, C., et al. (2010). A high-performance three-engine architecture for H.264/AVC fractional motion estimation. IEEE Transactions on Very Large Scale Integration Systems, 18(4), 662–666.Google Scholar
  16. 16.
    Lai, Y., et al. (2010). Hybrid parallel motion estimation architecture based on fast top-winners search algorithm. IEEE Transactions on Consumer Electronics, 56(3), 1837–1842.CrossRefGoogle Scholar
  17. 17.
    Cetin, M., et al. (2011). An adaptive true motion estimation algorithm for frame rate conversion of high definition video and its hardware implementations. IEEE Transactions on Consumers Electronics 57(2).Google Scholar
  18. 18.
    Altera Corporation. “Altera: The Programmable Solutions Company”. Available, from www.altera.com. Accessed Aug 2011.
  19. 19.
    ModelSim. Available, from www.model.com. Accessed Aug 2011.

Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Gustavo Sanchez
    • 1
  • Marcel Corrêa
    • 1
  • Diego Noble
    • 1
  • Marcelo Porto
    • 1
  • Sergio Bampi
    • 2
  • Luciano Agostini
    • 1
  1. 1.Group of Architectures and Integrated CircuitsFederal University of PelotasPelotasBrazil
  2. 2.Informatics InstituteFederal University of Rio Grande do SulPorto AlegreBrazil

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