Acceleration of the integer motion estimation in JEM through pre-analysis techniques

  • David García-Lucas
  • Gabriel Cebrián-Márquez
  • Antonio Jesús Díaz-Honrubia
  • Pedro Cuenca
Article
  • 19 Downloads

Abstract

ITU-T Video Coding Expert Group and ISO/IEC Moving Picture Expert Group are studying the potential need for standardization of the future video coding technology with a compression capability that significantly exceeds that of the current High Efficiency Video Coding (HEVC) standard, including its current extensions. Both groups are working together on this exploration activity in a collaboration effort known as Joint Video Exploration Team to evaluate compression technology designs proposed by their experts in this area. Preliminary results show that the new model achieves 25% bitrate reduction, but at a cost of extremely high computational complexity (11\(\times {}\)) with respect to HEVC. This paper proposes a pre-analysis algorithm designed to extract motion information of a frame, which is later used in the Motion Estimation (ME) module to speed up the encoder, showing that around 27% of the reference frames can be skipped and that more than 62% of the time is saved in the integer ME operation with a negligible impact of 0.11% in BD-rate.

Keywords

JEM Fast encoding Pre-analysis Computational cost 

Notes

Acknowledgements

This work was jointly supported by the Spanish Ministry of Economy and Competitiveness (MINECO) and the European Commission (FEDER funds) under the Project TIN2015-66972-C5-2-R, and by the Spanish Ministry of Education, Culture and Sports under the Grants FPU13/04601 and FPU16/05692.

References

  1. 1.
    ISO/IEC, ITU-T (2016) High efficiency video coding (HEVC). ITU-T Recommendation H.265 and ISO/IEC 23008-2 (version 4)Google Scholar
  2. 2.
    ISO/IEC, ITU-T (2017) Advanced video coding for generic audiovisual services. ITU-T Recommendation H.264 and ISO/IEC 14496-10 (version 12)Google Scholar
  3. 3.
    Ohm JR, Sullivan GJ, Schwarz H, Tan Thiow Keng, Wiegand T (2012) Comparison of the coding efficiency of video coding standards—including high efficiency video coding (HEVC). IEEE Trans Circuits Syst Video Technol 22(12):1669–1684.  https://doi.org/10.1109/TCSVT.2012.2221192 CrossRefGoogle Scholar
  4. 4.
    Cisco (2017) Cisco visual networking index: forecast and methodology, 2016–2021. https://www.cisco.com/c/en/us/solutions/collateral/service-provider/visual-networking-index-vni/complete-white-paper-c11-481360.html. Accessed 31 Jul 2017
  5. 5.
    Chen J, Alshina E, Sullivan GJ, Ohm JR, Boyce J (2016) Algorithm description of joint exploration test model 3. Technical Report JVET-C1001Google Scholar
  6. 6.
    Karczewicz M, Alshina E (2016) JVET AHG report: tool evaluation (AHG1). Technical Report JVET-D0001Google Scholar
  7. 7.
    Sullivan GJ, Ohm JR, Han Woo-Jin, Wiegand T (2012) Overview of the high efficiency video coding (HEVC) standard. IEEE Trans Circuits Syst Video Technol 22(12):1649–1668.  https://doi.org/10.1109/TCSVT.2012.2221191 CrossRefGoogle Scholar
  8. 8.
    Kim IK, Min J, Lee T, Han WJ, Park J (2012) Block partitioning structure in the HEVC standard. IEEE Trans Circuits Syst Video Technol 22(12):1697–1706.  https://doi.org/10.1109/TCSVT.2012.2223011 CrossRefGoogle Scholar
  9. 9.
    ISO/IEC, ITU-T (2017) Joint exploration test model (JEM) reference software. https://jvet.hhi.fraunhofer.de/. Accessed 15 Jan 2017
  10. 10.
    ISO/IEC, ITU-T (2016) HEVC test model (HM) reference software. https://hevc.hhi.fraunhofer.de/. Accessed 15 Jan 2017
  11. 11.
    Suehring K, Li X (2016) JVET common test conditions and software reference configurations. Technical Report JVET-B1010Google Scholar
  12. 12.
    Bjøntegaard G (2008) Improvements of the BD-PSNR model. Technical Report VCEG-AI11, 35th VCEG Meeting, ITU-T SG16 Q6Google Scholar
  13. 13.
    Cebrián-Márquez G, Hernández-Losada JL, Martínez JL, Cuenca P, Tang M, Wen J (2015) Accelerating HEVC using heterogeneous platforms. J Supercomput 71(2):613–628.  https://doi.org/10.1007/s11227-014-1313-8 CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Albacete Research Institute of Informatics (I3A)University of Castilla-La ManchaAlbaceteSpain

Personalised recommendations