Journal of Real-Time Image Processing

, Volume 16, Issue 1, pp 161–174 | Cite as

On predicting the HEVC intra quad-tree partitioning with tunable energy and rate-distortion

  • Alexandre MercatEmail author
  • Florian Arrestier
  • Maxime Pelcat
  • Wassim Hamidouche
  • Daniel Menard
Special Issue Paper


Future evolutions of the Internet of Things (IoT) are likely to boost mobile video demand to an unprecedented level. A large number of battery-powered systems will then integrate an High Efficiency Video Coding (Hevc) codec, implementing the latest video encoding standard from MPEG, and these systems will need to be energy efficient. Constraining the energy consumption of Hevc encoders is a challenging task, especially for embedded applications based on software encoders. The most efficient approach to manage the energy consumption of an Hevc encoder consists of optimizing the quad-tree partitioning and balance compression efficiency and energy consumption. The quad-tree partitioning splits the image into encoding units of variable sizes. The optimal size for a unit is content dependent and affects the encoding efficiency. Finding this optimal repartition is complex and the energy required by the so-called rate-distortion optimization (RDO) process dominates the encoder energy consumption. For the purpose of budgeting the energy consumption of a real-time Hevc encoder, we propose in this paper a variance-aware quad-tree prediction that limits the energetic cost of the RDO process. The predictor is moreover adjustable by two parameters, \((\underline{\varDelta }, \overline{\varDelta })\), offering a trade-off between energetic gains and compression efficiency. Experimental results show that the proposed energy reduction scheme is able to reduce the energy consumption of a real-time Hevc encoder by 45–62% for a bit rate increase of, respectively, 0.49 and 3.4%. Moreover, the flexibility offered by parameters \((\underline{\varDelta }, \overline{\varDelta })\) opens new opportunities for energy-aware encoding management.


Video encoding HEVC Energy reduction Quad-tree partitioning INTRA encoding 



This work is partially supported by the French ANR ARTEFaCT project, by COVIBE project funded by Brittany region and by the European Celtic-Plus project 4KREPROSYS funded by Finland, Flanders, France, and Switzerland. Funding was provided by INSA Rennes.


  1. 1.
    Biao, M., Cheung, R.C.C.: A fast CU size decision algorithm for the HEVC intra encoder. TCSVT 25(5), 892–896 (2015). Google Scholar
  2. 2.
    Bossen, F.: Common HM test conditions and software reference configurations, JCTVC-L1100. Switzerland, Geneva (2013)Google Scholar
  3. 3.
    Carroll, A., Heiser, G., et al. An Analysis of Power Consumption in a Smartphone. In: USENIX annual technical conference. 2010. pp 21–21Google Scholar
  4. 4.
    Cassa, M.B., Naccari, M., Pereira, F.: Fast rate distortion optimization for the emerging HEVC standard. In: Picture Coding Symposium (PCS), 2012, pp. 493–496. IEEE (2012)Google Scholar
  5. 5.
    Chan, T., Golub, G., et Leveque, R.: Updating formulae and a pairwise algorithm for computing sample variances. In : COMPSTAT 1982 5th Symposium held at Toulouse 1982. Physica, Heidelberg, 1982. pp. 30–41Google Scholar
  6. 6.
    Efraim, R., Alon, N., Doron, R., Avinash, A., Eliezer, W.: Power-management architecture of the intel microarchitecture code-named sandy bridge. IEEE Comput. Soc. 32(2), 20–27 (2012)Google Scholar
  7. 7.
    Feng, L., Dai, M., Cl, Zhao, Jy, Xiong: Fast prediction unit selection method for HEVC intra prediction based on salient regions. Optoelectron. Lett. 12(4), 316–320 (2016). CrossRefGoogle Scholar
  8. 8.
    Hackenberg, D., Schone, R., Ilsche, T., Molka, D., Schuchart, J., Geyer, R.: An Energy Efficiency Feature Survey of the Intel Haswell Processor, pp. 896–904. IEEE, Piscataway (2015). Google Scholar
  9. 9.
    JCT-VC (2016) HEVC reference software. Accessed 24 July 2018
  10. 10.
    Karczewicz, M., Ye, Y., Chong, I.: Rate distortion optimized quantization. In: VCEG-AH21, Antalya Turkey (2008)Google Scholar
  11. 11.
    Khan, M.U.K., Shafique, M., Henkel, J.: An adaptive complexity reduction scheme with fast prediction unit decision for HEVC intra encoding. In: ICIP, pp. 1578–1582. IEEE (2013)Google Scholar
  12. 12.
    Koivula, A., Viitanen, M., Lemmetti, A., Vanne, J., Hamalainen, T.D.: Performance evaluation of Kvazaar HEVC intra encoder on Xeon Phi many-core processor. In: 2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP), pp. 1250–1254. IEEE (2015)Google Scholar
  13. 13.
    Koivula, A., Viitanen, M., Vanne, J., Hamalainen, T.D., Fasnacht, L.: Parallelization of Kvazaar HEVC intra encoder for multi-core processors. In: 2015 IEEE Workshop on Signal Processing Systems (SiPS), pp. 1–6. IEEE (2015)Google Scholar
  14. 14.
    Lan, C., Xu, J., Sullivan, G.J., Wu, F.: Intra transform skipping. In: JCTVC-I0408, Geneva (2012)Google Scholar
  15. 15.
    Mercat, A., Arrestier, F., Hamidouche, W., Pelcat, M., Menard, D.: Energy reduction opportunities in an HEVC real-time encoder. In: 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE (2017)Google Scholar
  16. 16.
    Mercat, A., Arrestier, F., Pelcat, M., Hamidouche, W., Menard, D.: Prediction of Quad-Tree Partitioning for Budgeted Energy HEVC Encoding. In 2017 IEEE Workshop on: Signal Processing Systems (SiPS). IEEE (2017)Google Scholar
  17. 17.
    MulticoreWare (2017) x265 HEVC Encoder/H.265 Video Codec. Accessed 24 July 2018
  18. 18.
    Peng, K., Chiang, J., et Lie, W.: Low complexity depth intra coding combining fast intra mode and fast CU size decision in 3D-HEVC. In : Image Processing (ICIP), 2016 IEEE International Conference on. IEEE, pp. 1126–1130 (2016)Google Scholar
  19. 19.
    Penny, W., Machado, I., Porto, M., Agostini, L., Zatt, B.: Pareto-based energy control for the HEVC encoder. In: ICIP, pp. 814–818. IEEE (2016)Google Scholar
  20. 20.
    Qualcomm (2014) Snapdragon 810 processor product brief. Accessed 24 July 2018
  21. 21.
    Ruiz, D., Fernndez-Escribano, G., Adzic, V., Kalva, H., Martnez, J.L., Cuenca, P.: Fast CU partitioning algorithm for HEVC intra coding using data mining. Multimed. Tools Appl. 76(1), 861–894 (2015). CrossRefGoogle Scholar
  22. 22.
    Shen, L., Zhang, Z., An, P.: Fast CU size decision and mode decision algorithm for HEVC intra coding. Consum. Electron. IEEE Trans. 59(1), 207–213 (2013)CrossRefGoogle Scholar
  23. 23.
    Sullivan, G.J., Ohm, J.R., Han, W.J., Wiegand, T.: Overview of the high efficiency video coding (HEVC) standard. IEEE Trans. Circuits Syst. Video Technol. 22(12), 1649–1668 (2012). CrossRefGoogle Scholar
  24. 24.
    Sze, V., Budagavi, M., Sullivan, G.J. (eds.): High Efficiency Video Coding (HEVC). Integrated Circuits and Systems. Springer International Publishing, Cham (2014)Google Scholar
  25. 25.
    Tan, T.K., Weerakkody, R., Mrak, M., Ramzan, N., Baroncini, V., Ohm, J.R., Sullivan, G.J.: Video quality evaluation methodology and verification testing of HEVC compression performance. TCSVT 26(1), 76–90 (2016). Google Scholar
  26. 26.
    Ultra Video Group (2017) Kvazaar HEVC encoder. Accessed July 2018
  27. 27.
    Vanne, J., Viitanen, M., Hamalainen, T.D., Hallapuro, A.: Comparative rate-distortion-complexity analysis of HEVC and AVC video codecs. IEEE Trans. Circuits Syst. Video Technol. 22(12), 1885–1898 (2012). CrossRefGoogle Scholar
  28. 28.
    Vantrix (2017) F265 open source HEVC/H.265 project. Accessed July 2018
  29. 29.
    Viitanen, M., Koivula, A., Lemmetti, A., Vanne, J., Hamalainen, T.D.: Kvazaar HEVC encoder for efficient intra coding. In: ISCAS, pp. 1662–1665. IEEE (2015)Google Scholar
  30. 30.
    Wang, X., Xue, Y.: Fast HEVC intra coding algorithm based on Otsu’s method and gradient. In: BMSB, pp. 1–5. IEEE (2016)Google Scholar
  31. 31.
    Wiegand, T., Sullivan, G., Bjontegaard, G., Luthra, A.: Overview of the H.264/AVC video coding standard. IEEE Trans. Circuits Syst. Video Technol. 13(7), 560–576 (2003). CrossRefGoogle Scholar
  32. 32.
    Wien, M.: High Efficiency Video Coding. Signals and Communication Technology. Springer, Berlin, Heidelberg (2015)Google Scholar
  33. 33.
    Zhang, J., Li, B., Li, H.: An efficient fast mode decision method for inter prediction in HEVC. IEEE Trans. Circuits Syst. Video Technol. 22(8), 1502–1515 (2015). Google Scholar
  34. 34.
    Khan, M.U.K., Shafique, M, Henkel, J.: Energy efficient embedded video processing systems, A hardware-software collaborative approach. Springer (2017)Google Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Alexandre Mercat
    • 1
    Email author
  • Florian Arrestier
    • 1
  • Maxime Pelcat
    • 1
    • 2
  • Wassim Hamidouche
    • 1
  • Daniel Menard
    • 1
  1. 1.INSA Rennes, IETR, UMR CNRS 6164, UEBRennesFrance
  2. 2.Institut Pascal, CNRS UMR 6602Clermont-FerrandFrance

Personalised recommendations