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Low-complexity heterogeneous architecture for H.264/HEVC video transcoding

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Abstract

High efficiency video coding (HEVC) was developed by the Joint Collaborative Team on video coding to replace the current H.264/AVC standard, which has been widely adopted over the last few years. Therefore, there is a lot of legacy content encoded with H.264/AVC, and an efficient conversion to HEVC is needed. This paper presents a hybrid transcoding algorithm which makes use of soft computing techniques as well as parallel processing. On the one hand, a fast quadtree level decision algorithm tries to exploit the information gathered at the H.264/AVC decoder to make faster decisions on coding unit splitting in HEVC using a Naïve–Bayes probabilistic classifier that is determined by a supervised data mining process. On the other hand, a parallel HEVC-encoding algorithm makes use of a heterogeneous platform composed of a multi-core central processing unit plus a graphics processing unit (GPU). In this way, from a coarse point of view, groups of frames or rows of a frame (both options are possible) are divided into threads to be executed on each core (each of which executes one of the aforementioned classifiers) and, from a finer point of view, all these threads work in a collaborative way on a single GPU to perform the motion estimation process on the co-processor. Experimental results show that the proposed transcoder can achieve a good tradeoff between coding efficiency and complexity compared with the anchor transcoder.

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Notes

  1. A value of 2.0 means that we have estimated that the cost of wrongly classifying \(C_S\) as \(C_N\) is twice that of the contrary error. This type of error at high levels (0 or 1) can have a great impact on the output sequence, because subsequent low-level splitting is not considered.

References

  1. Bjontegaard, G.: Improvements of the BD- PSNR model. ITU-T SG16 Q 6, 35 (2008)

  2. Bossen, F.: Common HM test conditions and software reference configurations. In: Proceedings of 12th JCT-VC Meeting, Doc. JCTVC-L1100 (2013)

  3. Bossen, F., Bross, B., Suhring, K., Flynn, D.: HEVC complexity and implementation analysis. IEEE Trans. Circuits Syst. Video Technol. 22(12), 1685–1696 (2012). doi:10.1109/TCSVT.2012.2221255

    Article  Google Scholar 

  4. Bross, B., Han, W., Ohm, J., Sullivan, G., Wang, Y.K., Wiegand, T.: High efficiency video coding (HEVC) text specification draft 10. Doc. JCTVC-L1003 (2013)

  5. Cheung, N.M., Fan, X., Au, O., Kung, M.C.: Video coding on multicore graphics processors. Sig. Process. Mag. IEEE 27(2), 79–89 (2010). doi:10.1109/MSP.2009.935416

    Article  Google Scholar 

  6. Chi, C.C., Alvarez-Mesa, M., Juurlink, B., Clare, G., Henry, F., Pateux, S., Schierl, T.: Parallel scalability and efficiency of hevc parallelization approaches. Circuits Syst. Video Technol. IEEE Trans. 22(12), 1827–1838 (2012)

    Article  Google Scholar 

  7. Corrales-Garcia, A., Martinez, J.L., Fernandez-Escribano, G., Quiles, F.J.: Variable and constant bitrate in a DVC to H.264/avc transcoder. Sig. Process. Image Commun. 26(6), 310–323 (2011)

    Article  Google Scholar 

  8. Fayyad, U.M., Irani, K.B.: Multi-Interval discretization of continuous-valued attributes for classification learning. In: Proceedings of the International Joint Conference on Uncertainty in AI, pp. 1022–1027 (1993)

  9. Feng, C.W., Manocha, D.: High-performance computing using accelerators. Parallel computing 33(10–11), 645–647 (2007). http://dblp.uni-trier.de/db/journals/pc/pc33.html#FengM07

  10. Fernandez-Escribano, G., Bialkowski, J., Gamez, J., Kalva, H., Cuenca, P., Orozco-Barbosa, L., Kaup, A.: Low-complexity heterogeneous video transcoding using data mining. IEEE Trans. Multimed. 10(2), 286–299 (2008)

    Article  Google Scholar 

  11. Fernandez-Escribano, G., Kalva, H., Cuenca, P., Orozco-Barbosa, L., Garrido, A.: A fast mb mode decision algorithm for MPEG-2 to H.264 p-frame transcoding. IEEE Trans. Circuits Syst. Video Technol. 18(2), 172–185 (2008)

    Article  Google Scholar 

  12. Flores, J., Gámez, J.A., Martínez, A.M.: Supervised classification with Bayesian networks. In: Intelligent data analysis for real-life applications: theory and practice, pp. 72–102 (2012)

  13. Garrido-Cantos, R., De Cock, J., Martinez, J., Vanleuven, S., Cuenca, P.: Motion-based temporal transcoding from H.264/ AVC-to- SVC in baseline profile. Consum. Electr. IEEE Trans. 57(1), 239–246 (2011)

    Article  Google Scholar 

  14. Guyon, I., Elisseeff, A.: An introduction to variable and feature selection. J. Mach. Learn. Res. 3, 1157–1182 (2003)

    MATH  Google Scholar 

  15. Henry, F., Pateux, S.: Wavefront parallel processing. Tech. Rep. JCTVC-E196 (2011)

  16. HM reference software. http://hevc.hhi.fraunhofer.desvnsvn.HEVCSoftware

  17. ITU-T, JTC, I.: Advanced video coding for generic audiovisual services. ITU-T Rec. H.264 and ISO/IEC 14496–10 (AVC) version 16 (2012)

  18. Joint collaborative team on video coding: reference software to Committee Draft, version 18.4 (2012)

  19. Lopez-Granado, O.M., Malumbres, M.P., Migallón, H., Piñol, P.J.: Analyzing GOP-based parallel strategies with the HEVC encoder. In: Proceedings of the 13th International Conference Computational and Mathematical Methods in Science and Engineering (2013)

  20. Misra, K., Segall, A., Horowitz, M., Xu, S., Fuldseth, A., Zhou, M.: An overview of tiles in hevc. IEEE J. Sel. Topics Sig. Process. 7(6), 969–977 (2013). doi:10.1109/JSTSP.2013.2271451

    Article  Google Scholar 

  21. NVIDIA: NVIDIA CUDA compute unified device architecture programming guide, version 3.2 (2010)

  22. Ohm, J., Sullivan, G., Schwarz, H., Tan, T.K., Wiegand, T.: 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 (2012)

    Article  Google Scholar 

  23. Patnaik, S., Yang, Y.M.: Soft computing techniques in vision science, vol. 395. Springer (2012)

  24. Peixoto, E., Izquierdo, E.: A complexity-scalable transcoder form H.264/ AVC to the new HEVC codec. In: International Conference on Image Processing (ICIP), Orlando, FL, USA (September 2012) (2012)

  25. Peixoto, E., Shanableh, T., Izquierdo, E.: H.264/ AVC to HEVC video transcoder based on dynamic thresholding and content modeling. IEEE Trans. Circuits Syst. Video Technol 24(1), 99–112 (2014)

    Article  Google Scholar 

  26. Shen, T., Lu, Y., Wen, Z., Zou, L., Chen, Y., Wen, J.: Ultra fast H.264/ AVC to HEVC transcoder. In: Data Compression Conference (DCC), 2013, pp. 241–250 (2013)

  27. Su, H., Wu, N., Zhang, C., Wen, M., Ren, J.: A multilevel parallel intra coding for H.264/AVC based on CUDA. In: Image and Graphics (ICIG), 2011 Sixth International Conference on, pp. 76–81 (2011) doi:10.1109/ICIG.2011.99

  28. 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)

    Article  Google Scholar 

  29. Vetro, A., Christopoulos, C., Sun, H.: Video transcoding architectures and techniques: an overview. IEEE Sig. Process. Mag. 20(2), 18–29 (2003)

    Article  Google Scholar 

  30. Wang, X., Song, L., Chen, M., Yang, J.: Paralleling variable block size motion estimation of HEVC on CPU plus GPU platform. IEEE Int. Conf. Multimed. Expo Workshops (ICMEW) 2013, 1–5 (2013). doi:10.1109/ICMEW.2013.6618412

    Google Scholar 

  31. Yan, C., Dai, F., Zhang, Y.: Parallel deblocking filter for H.264/AVC on the TILERA many-core systems. In: Advances in Multimedia Modeling, Lecture Notes in Computer Science, vol. 6523, pp. 51–61. Springer, Berlin (2011). doi:10.1007/978-3-642-17832-0_6

  32. Yan, C., Zhang, Y., Dai, F., Li, L.: Highly parallel framework for HEVC motion estimation on many-core platform. Data Compress. Conf. (DCC) 2013, 63–72 (2013). doi:10.1109/DCC.2013.14

    Google Scholar 

  33. Yu, Q., Zhao, L., Ma, S.: Parallel AMVP candidate list construction for HEVC. In: Visual communications and image processing (VCIP), 2012 IEEE, pp. 1–6 (2012). doi:10.1109/VCIP.2012.6410775

  34. Zhang, D., Li, B., Xu, J., Li, H.: Fast transcoding from H.264 avc to high efficiency video coding. In: IEEE International Conference on Multimedia and Expo (ICME) 2012, pp. 651–656 (2012)

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Correspondence to Antonio Jesús Díaz-Honrubia.

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This work has been jointly supported by the MINECO and European Commission (FEDER funds) under the projects TIN2012-38341-C04-04, TIN2010-20900-C04-03 and TIN2013-46638-C3-3-P. Likewise, this work has also been supported by the Spanish Ministry of Education, Culture and Sports under Grants FPU 12/00994 and FPU 13/04601.

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Díaz-Honrubia, A.J., Cebrián-Márquez, G., Martínez, J.L. et al. Low-complexity heterogeneous architecture for H.264/HEVC video transcoding. J Real-Time Image Proc 12, 311–327 (2016). https://doi.org/10.1007/s11554-014-0477-z

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