Advertisement

Multimedia Tools and Applications

, Volume 78, Issue 1, pp 1035–1051 | Cite as

A novel adaptive fast partition algorithm based on CU complexity analysis in HEVC

  • Mengmeng ZhangEmail author
  • Delun Lai
  • Zhi Liu
  • Changzhi An
Article
  • 58 Downloads

Abstract

High efficiency video coding (HEVC) is the latest video coding standard. Compared with H.264, the proposal of quad-tree structure not only improves the coding efficiency greatly but also increases complexity of coding. Therefore, this paper performed a fast-adaptive algorithm based on the complexity of images for intra prediction. Two values from micro and macro levels are considered for each coding unit block. We use entropy on the macroscopic level and texture contrast on the microscopic level. Relatively, large pictures always have more smooth blocks and there are more complex blocks in small pictures. To deal with this problem, this study uses adaptive process to make the values of entropy and texture contrast close to the ideal values of the current video, thereby making the division reasonable. Experimental results show that the proposed algorithm can reduce 34.6% coding time on average, with a loss of Bjøntegaard delta rate of 0.8%.

Keywords

HEVC Entropy Texture contrast Unit coding Adaptive 

Notes

Acknowledgements

This work is supported by the National Natural Science Foundation of China (No.61370111), Beijing Municipal Natural Science Foundation (No.4172020), Great Wall Scholar Project of Beijing Municipal Education Commission (CIT&TCD20180304), Beijing Youth Talent Project (CIT&TCD 201504001), and Beijing Municipal Education Commission General Program (KM201610009003).

References

  1. 1.
    Bai HH, Zhu C, Zhao Y (2007) Optimized multiple description lattice vector quantization for wavelet image coding. IEEE Trans Circ Syst Video Tech 17:912–917CrossRefGoogle Scholar
  2. 2.
    Bai HH, Lin WS, Zhang MM, Wang AH, Zhao Y (2014) Multiple description video coding based on human visual system characteristics. IEEE Trans Circ Syst Video Tech 24:1390–1394CrossRefGoogle Scholar
  3. 3.
    Chen YQ, Duan J, Zhu Y, Qian XF, Xiao B (2015) Research on the image complexity based on neural network. International Conference on Machine Leaning and Cybernetics (ICMLC) 1:295–300Google Scholar
  4. 4.
    Chen Y, Bordes P, Poirier T, Racape F (2017) Optimization of sample adaptive band offset in HEVC. Data Compression Conference (DCC) 2017:434–434Google Scholar
  5. 5.
    Detlev M, Heiko S, Sebastian B, Benjamin B, Philipp H (2010) Video compression using nested Quadtree structures, leaf merging, and improved techniques for motion representation and entropy coding. IEEE Trans Circ Syst Video Tech 20:1676–1687CrossRefGoogle Scholar
  6. 6.
    Fang MY, Wen JT (2017) Probabilistic graphical model based fast HEVC inter prediction. IEEE Data Compression Conference, Snowbird, pp 439–439Google Scholar
  7. 7.
    Han WJ, Min J, Kim IK (2010) Improved video compression efficiency through flexible unit representation and corresponding extension of coding tools. IEEE Trans Circ Syst Video Tech 20:1709–1720CrossRefGoogle Scholar
  8. 8.
    Huang H, Wei F (2016) Fast algorithm based on edge density and gradient angle for intra encoding in HEVC. IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC) 347–351Google Scholar
  9. 9.
    Kim IK, Min J, lee T, Han WJ, Park J (2012) Block partitioning structure in the HEVC standard. IEEE Trans Circ Syst Video Tech 22:1697–1706CrossRefGoogle Scholar
  10. 10.
    Kim YH, Kim TS, Sunwoo MH, Jeong JH (2016) Fast CU size decision method for HEVC using CU split information of adjacent frames. International SoC Design Conference (ISOCC) 331–332Google Scholar
  11. 11.
    Lainema J, Bossen F, Han WJ, Min J, Ugur K (2012) Intra coding of the HEVC standard. IEEE Trans Circ Syst Video Tech 22:1792–1801CrossRefGoogle Scholar
  12. 12.
    Li F, Jiao DD, Shi GM, Niu Y, Fan CX, Xie XM (2017) An AR based fast mode decision for H.265/HEVC intra coding. Multimedia Tools and Applications 76:13107–13125CrossRefGoogle Scholar
  13. 13.
    Liu XG, Liu YB, Wang PC, Lai CF, Chao HC (2017) An adaptive mode decision algorithm based on video texture characteristics for HEVC intra prediction. IEEE Trans Circ Syst Video Tech 27:1737–1748CrossRefGoogle Scholar
  14. 14.
    Nikolett B, Amalia D, Krisztian N, Salvador R (2016) Quad-kd trees: a general framework kd trees and quad trees. Theor Comput Sci 616:126–140CrossRefGoogle Scholar
  15. 15.
    Pakdaman F, Hashemi MR, Ghanbari M (2017) Fast and efficient intra mode decision for HEVC, based on dual-tree complex wavelet. Multimedia Tools and Applications 76:9891–9906CrossRefGoogle Scholar
  16. 16.
    Qin J, Bai HH, Zhang MM, Zhao Y (2017) Fast intra coding algorithm for HEVC based on decision tree. IEICE Trans Fundam Electron Commun Comput Sci E100A:1274–1278CrossRefGoogle Scholar
  17. 17.
    Saldanha M, Sanchez G, Zatt B, Porto M, Agostini L (2017) Energy-aware scheme for the 3D-HEVC depth maps prediction. J Real-Time Image Proc 13:55–69CrossRefGoogle Scholar
  18. 18.
    Sullivan GJ, Ohm JR, Han WJ, Wiegand T (2012) Overview of the high efficiency video coding (HEVC) standard. IEEE Trans Circ Syst Video Tech 22:1649–1668CrossRefGoogle Scholar
  19. 19.
    Wang C (2017) G Feng, fast mode decision algorithm for depth map intra coding in 3D-HEVC. Computer Engineering and Application 53:206–210Google Scholar
  20. 20.
    Wang XJ, Xue YL (2017) Fast HEVC Inter Prediction Algorithm Based on Spatio-Temporal Block Information. International symposium on broadband multimedia systems and broadcasting (BMSB), Cagliari, pp 153–157Google Scholar
  21. 21.
    Xiao W, B Li JZX, GM Shi FW (2018) Weighted rate-distortion optimization for screen content coding. IEEE Trans Circ Syst Video Tech 28:499–512CrossRefGoogle Scholar
  22. 22.
    Xie X, Xin X, Wang H (2017) A fast coding unit division and mode selection method for HEVC intra prediction. 4th International Conference on Systems and Informatics (ICSAI) 1302–1307Google Scholar
  23. 23.
    Xiong L, Zhou W, Zhou X, Zhang G, Qing A (2016) Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA) 1–5Google Scholar
  24. 24.
    Xu Z, Mei L, Liu Y, Hu C, Chen L (2016) Semantic enhanced cloud environment for surveillance data management using video structural description. Computing 98(1–2):35–54MathSciNetCrossRefGoogle Scholar
  25. 25.
    Ye J, Ding Y (2018) Controllable keyword search scheme supporting multiple users. Future Generation Comp Syst 81:433–442CrossRefGoogle Scholar
  26. 26.
    Zhang QW, Yang YS, Chang HW, Zhang WW, Gan Y (2017) Fast intra mode decision for depth coding in 3D-HEVC. Multidim Syst Sign Process 28:1203–1226MathSciNetCrossRefGoogle Scholar
  27. 27.
    Zhang T, Sun MT, Zhao DB, Gao W (2017) Fast intra-mode and CU size decision for HEVC. IEEE Trans Circ Syst Video Tech 27:1714–1726CrossRefGoogle Scholar
  28. 28.
    Zhou JB, Zhou DJ, Wang SH, Zhang SP, Yoshimura T, Goto S (2017) A dual-clock VLSI Design of H.265 sample adaptive offset estimation for 8k ultra-HD TV encoding. IEEE Trans on Very Large Scale Integration (VLSI) Systems 25:714–724CrossRefGoogle Scholar
  29. 29.
    Zhu WJ, Zhang K, An JC, Huang H, Sun YC, Huang YW, Lei SM (2017) Inter-Palette in Screen Content Coding. IEEE Trans on Broadcasting 63:673–679CrossRefGoogle Scholar

Copyright information

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

Authors and Affiliations

  • Mengmeng Zhang
    • 1
    Email author
  • Delun Lai
    • 1
  • Zhi Liu
    • 1
  • Changzhi An
    • 2
  1. 1.North China University of TechnologyBeijingChina
  2. 2.Beijing China Electronic Intelligent Communication Technology Co., Ltd.BeijingChina

Personalised recommendations