An enhanced performance for H.265/SHVC based on combined AEGBM3D filter and back-propagation neural network

Original Paper

Abstract

This paper deals with primary latest video coding standard H.265/SHVC, a scalable extension to High Efficiency Video Coding (HEVC). HEVC introduces new coding tools compared to its predecessor and is backward compatible to all type of electronic gadgets. The gadgets with different display capabilities cannot be offered the same quality video due to the constraints in transmission bandwidth is a major problem. One solution to this problem will be compression of video sequence which is focused in this paper to preserve or increase PSNR while reducing bit-rate besides a novel method implemented in SHVC encoder. The novel method undergoes a combined AEGBM3D (adaptive edge guided block matching and 3D) filtering and back-propagation technique. The technique includes an AEGBM3D filter which avoids spatial redundancy and de-noise frames; hence enhancement in PSNR is achieved. The obtained PSNR of the video is compared with the set threshold PSNR so as to maintain PSNR above the threshold by repeated AEGBM3D filtering. The BP technique based on neural network machine learning approach continually restrains the output if the input block does not contain a feature they were trained to recognize. This frequent control over the output produces few bits; hence reduction in bit-rate is achieved. The simulation results show that the proposed technique delivers an average increment of 0.16 and 0.25 dB in PSNR and an average decrement of 28 and 37% in bit-rate for \(\times \)1.5 and \(\times \)2 spatial ratios, respectively, compared with the existing methods.

Keywords

H.265 SHVC Back-propagation AEGBM3D filter PSNR Bit-rate Neural network 

References

  1. 1.
    Pourazad, M.T., Doutre, C., Azimi, M., Nasiopoulos, P.: HEVC: the new gold standard for video compression. IEEE Consum. Electron. Mag. 1(3), 36–46 (2012)CrossRefGoogle Scholar
  2. 2.
    Test Model for Scalable Extensions of High Efficiency Video Coding (HEVC). In: ISO/IEC and JTC1/SC29/WG11 (2013)Google Scholar
  3. 3.
    Sze, V., Budagavi, M., Madhukar, S., Sullivan, G.: High Efficiency Video Coding (HEVC): Algorithms and Architectures, Integrated Circuits and Systems. Springer, New York (2014)CrossRefGoogle Scholar
  4. 4.
    Wien, M.: High Efficiency Video Coding: Coding Tools and Specification. Signals and Communication Technology. Springer, Berlin (2014)Google Scholar
  5. 5.
    Sullivan, G.J., Ohm, J., Woo-Jin, J.H., Wiegand, T.: Overview of the high efficiency video coding (HEVC) standard. IEEE Trans. Circuits Syst. Video Technol. 22(12), 1649–1668 (2012)CrossRefGoogle Scholar
  6. 6.
    Schwarz, A.H., Marpe, D., Wiegand, T.: Overview of the scalable video coding extension of the H.264/AVC standard. IEEE Trans. Circuits Syst. Video Technol. 17(9), 1103–1120 (2007)CrossRefGoogle Scholar
  7. 7.
    Zhang, H., Ma, Z.: Fast intra mode decision for high efficiency video coding (HEVC). IEEE Trans. Circuits Syst. Video Technol. 24(4), 660–668 (2014)CrossRefGoogle Scholar
  8. 8.
    Cho, S., Kim, M.: Fast CU splitting and pruning for suboptimal CU partitioning in HEVC intra coding. IEEE Trans. Circuits Syst. Video Technol. 23(9), 1555–1564 (2013)CrossRefGoogle Scholar
  9. 9.
    Shen, L., Liu, Z., Zhang, X., Zhao, W., Zhang, Z.: An effective CU size decision method for HEVC encoders. IEEE Trans. Multimed. 15(2), 465–470 (2013)CrossRefGoogle Scholar
  10. 10.
    Xu, Y., Li, Q., Chen, J., Zhao, T.: Adaptive search range control in H.265/HEVC with error propagation resilience and hierarchical adjustment. SIViP 11, 1559–1566 (2017)CrossRefGoogle Scholar
  11. 11.
    Li, W., Zhao, F., Zhang, E., Ren, P.: Lagrange optimization in high efficiency video coding for SATD-based intra-mode decision. SIViP 11, 1163–1170 (2017)CrossRefGoogle Scholar
  12. 12.
    Pan, Z., Kwong, S., Sun, M.T., Lei, J.: Early MERGE mode decision based on motion estimation and hierarchical depth correlation for HEVC. IEEE Trans. Broadcast. 60(2), 405–412 (2014)CrossRefGoogle Scholar
  13. 13.
    Hu, N., Yang, E.H.: Fast motion estimation based on confidence interval. IEEE Trans. Circuits Syst. Video Technol. 24(8), 1310–1322 (2014)CrossRefGoogle Scholar
  14. 14.
    Xiong, J., Li, H., Wu, Q., Meng, F.: A fast HEVC inter CU selection method based on pyramid motion divergence. IEEE Trans. Multimed. 16(2), 559–564 (2014)CrossRefGoogle Scholar
  15. 15.
    Shen, L., Liu, Z., Zhang, X., Zhaoyang, Z.: An effective decision method for HEVC encoders. IEEE Trans. Multimed. 15(2), 465–470 (2013)CrossRefGoogle Scholar
  16. 16.
    Shen, L., Zhang, Z., Liu, Z.: Adaptive inter-mode decision for HEVC jointly utilizing inter-level and spatiotemporal correlations. IEEE Trans. Circuits Syst. Video Technol. 24(10), 1709–1722 (2014)CrossRefGoogle Scholar
  17. 17.
    Shen, L., Zhang, Z., An, P.: Fast CU size decision and mode decision algorithm for HEVC intra coding. IEEE Trans. Consum. Electron. 59(1), 207–213 (2013)CrossRefGoogle Scholar
  18. 18.
    Shen, L., Zhang, Z., Liu, Z.: Effective CU size decision for HEVC intracoding. IEEE Trans. Image Process. 23(10), 4232–4241 (2014)MathSciNetCrossRefMATHGoogle Scholar
  19. 19.
    Tohidypour, H.R., Pourazad, M.T., Nasiopoulos, P.: Content adaptive complexity reduction scheme for quality/fidelity scalable HEVC. In: Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (2013)Google Scholar
  20. 20.
    Content Adaptive Complexity Reduction Scheme for Quality/Fidelity Scalable HEVC. In: ISO/IEC and JTC1/SC29/WG11, L0042 (2013)Google Scholar
  21. 21.
    Tohidypour, H.R., Pourazad, M.T., Bashashati, H., Nasiopoulos, P.: Fast mode assignment for quality scalable extension of the high efficiency video coding (HEVC) standard: a Bayesian approach. In: Proceedings of the 6th Balkan Conference in Informatics (2013)Google Scholar
  22. 22.
    Tohidypour, H.R., Pourazad, M.T., Nasiopoulos, P.: Adaptive search range method for spatial scalable HEVC. In: Proceedings of the IEEE International Conference on Consumer Electronics (2014)Google Scholar
  23. 23.
    Zuo, X., Yu, L.: Fast mode decision method for all intra spatial scalability in SHVC. In: Proceedings of the IEEE Visual Communications and Image Processing (2014)Google Scholar
  24. 24.
    Huang, D.S., Bevilacqua, V., Premaratne, P. (eds.): Intelligent Computing Theory. Fast Mode and Depth Decision Algorithm for Intra Prediction of Quality SHVC. Springer, Cham (2014)Google Scholar
  25. 25.
    Bailleul, R., De Cock, J., Van de Walle, R.: Fast mode decision for SNR scalability in SHVC digest of technical papers. In: Proceedings of the IEEE International Conference on Consumer Electronics (2014)Google Scholar
  26. 26.
    Aminlou, A., Lainema, J., Ugur, K., Hannuksela, M.M., Gabbouj, M.: Differential coding using enhanced inter-layer reference picture for the scalable extension of H.265/HEVC video codec. IEEE Trans. Circuits Syst. Video Technol. 24(11), 1945–1956 (2014)CrossRefGoogle Scholar
  27. 27.
    Tohidypour, H.R., Pourazad, M.T., Nasiopoulos, P.: Probabilistic approach for predicting the size of coding units in the quad-tree structure of the quality and spatial scalable HEVC. IEEE Trans. Multimed. 18(2), 182–195 (2016)CrossRefGoogle Scholar
  28. 28.
    Tohidypour, H.R., Pourazad, M.T., Nasiopoulos, P.: An encoder complexity reduction scheme for quality/fidelity scalable HEVC. IEEE Trans. Broadcast. 62(3), 664–674 (2016)CrossRefGoogle Scholar
  29. 29.
    Biatek, T., Hamidouche, W., Travers, J.F., Deforges, O.: Optimal bitrate allocation in the scalable HEVC extension for the deployment of UHD services. IEEE Trans. Broadcast. 62(4), 826–841 (2016)CrossRefGoogle Scholar
  30. 30.
    Dabov, K., Foi, F., Katkovnik, V., Egiazarian, K.: Image denoising by sparse 3D transform-domain collaborative filtering. IEEE Trans. Image Process. 16(8), 2080–2095 (2007)MathSciNetCrossRefGoogle Scholar
  31. 31.
    Dabov, K., Foi, A., Egiazarian, K.: Video denoising by sparse 3D transform-domain collaborative filtering. In: Proceedings of the 15th European Signal Processing Conference (2007)Google Scholar
  32. 32.

Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Faculty of Information and communicationAnna UniversityChennaiIndia
  2. 2.Department of ECEVelammal Institute of TechnologyChennaiIndia
  3. 3.RMD Engineering CollegeChennaiIndia

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