Multimedia Tools and Applications

, Volume 76, Issue 1, pp 1439–1453 | Cite as

A fuzzy rate controller for variable bit rate video using foveated just-noticeable distortion model

  • Mehdi Rezaei
  • Effat Karimghasemi


In this paper, a rate control algorithm for variable bit rate video applications with buffer constraint is proposed. The proposed algorithm utilizes a fuzzy rate controller and a perceptual quality controller. The fuzzy controller computes a base quantization parameter (QP) for each video picture to provide the buffer constraint. Then, the perceptual quality controller uses a human visual system (HVS) model namely foveated just-noticeable distortion (FJND) model to improve the perceptual quality of encoded video by modulating the QP of macroblocks around the picture QP. The proposed rate control algorithm has been implemented on the JM H.264/AVC reference software and obtained experimental results show that it can produce encoded videos with high perceptual quality while the buffering constraint is strongly obeyed.


Bit rate Control FNJD Fuzzy Human visual system (HVS) H.264/AVC standard Variable Video coding 


  1. 1.
    Chen Z, Guillemot C (2010) Perceptually-friendly H. 264/AVC video coding based on foveated just-noticeable-distortion model. IEEE Trans Circuits Syst Video Technol 20:806–819CrossRefGoogle Scholar
  2. 2.
    Chen Z, Liu H (2014) JND modeling: approaches and applications. Digital Signal Processing (DSP), 2014 19th International Conference on, 20–23 AuguestGoogle Scholar
  3. 3.
    Chou C-H, Chen C-W (1996) A perceptually optimized 3-D subband codec for video communication over wireless channels. IEEE Trans Circuits Syst Video Technol 6:143–156CrossRefGoogle Scholar
  4. 4.
    Gary S, Wiegand T, Lim KP (2003) Joint model reference encoding methods and decoding concealment methods; Section 2.6: Rate Control, JVT-I049. San Diego, SeptemberGoogle Scholar
  5. 5.
    Hrarti M, Saadane H, Larabi M, Tamtaoui A, Aboutajdine D (2010) A macroblock-based perceptually adaptive bit allocation for H264 rate control. In: I/V Communications and Mobile Network (ISVC), 2010 5th International Symposium on, pp. 1–4Google Scholar
  6. 6.
    Lakshman T, Ortega A, Reibman AR (1998) VBR video: tradeoffs and potentials. Proc IEEE 86:952–973CrossRefGoogle Scholar
  7. 7.
    Liu H, Chen Z (2015) Exploiting perceptual redundancy in images. Visual Information Processing and Communication VI, SPIE Proceedings, Vol. 9410Google Scholar
  8. 8.
    Liu Y, Li ZG, Soh YC (2008) Region-of-interest based resource allocation for conversational video communication of H. 264/AVC. IEEE Trans Circuits Syst Video Technol 18:134–139CrossRefGoogle Scholar
  9. 9.
    Luo Z, Song L, Zheng S, Ling N (2013) H.264/advanced video control perceptual optimization coding based on JND-directed coefficient suppression. IEEE Trans Circuits Syst Video Technol 20(6):935–948CrossRefGoogle Scholar
  10. 10.
    Naccari M, Pereira F (2011) Advanced H.264/AVC-based perceptual video coding: architecture, tools, and assessment. IEEE Trans Circuits Syst Video Technol 21(6):766–782CrossRefGoogle Scholar
  11. 11.
    Netravali AN, Prasada B (1977) Adaptive quantization of picture signals using spatial masking. Proc IEEE 65(4):536–548CrossRefGoogle Scholar
  12. 12.
    Nguyen AG, Hwang J-N (2002) SPEM online rate control for realtime streaming video. In: Information technology: Coding and computing. Proceedings. International Conference on, pp. 65–70Google Scholar
  13. 13.
    Reed EC, Dufaux F (2001) Constrained bit-rate control for very low bit-rate streaming-video applications. IEEE Trans Circuits Syst Video Technol 11:882–889CrossRefGoogle Scholar
  14. 14.
    Rezaei M, Hannuksela MM, Gabbouj M (2008) Semi-fuzzy rate controller for variable bit rate video. IEEE Trans Circuits Syst Video Technol 18:633–645CrossRefGoogle Scholar
  15. 15.
    Ruolin R, Ruimin H, Zhongming L (2011) A novel rate control algorithm of video coding based on visual perceptual characteristic. In: Computer Science & Education (ICCSE), 2011 6th International Conference on, pp. 843–846Google Scholar
  16. 16.
    Shang X, Wang Y, Luo L, Zhang Z (2013) Perceptual multiview video coding based on foveated just noticeable distortion profile in DCT domain. In: Image Processing (ICIP), 2013 20th IEEE International Conference on, 15–18 SeptemberGoogle Scholar
  17. 17.
    T. M. E. Committee (1993) MPEG-2 test model 5, Rev. 2, Section 10: Rate Control and Quantization Optimization, ISO/IEC/JTC1SC29WG11, AprilGoogle Scholar
  18. 18.
    Takamura S, Kobayashi N (2001) MPEG-2 one-pass variable bit rate control algorithm and its LSI implementation. In: Image Processing (ICIP), 2001 8th International Conference on, pp. 942–945Google Scholar
  19. 19.
    Tang C-W (2007) Spatiotemporal visual considerations for video coding. IEEE Trans Multimedia 9:231–238CrossRefGoogle Scholar
  20. 20.
    Tang C-W, Chen C-H, Yu Y-H, Tsai C-J (2006) Visual sensitivity guided bit allocation for video coding. IEEE Trans Multimedia 8:11–18CrossRefGoogle Scholar
  21. 21.
    Wandell BA (1995) Foundations of vision. Sinauer Associates, SunderlandGoogle Scholar
  22. 22.
    Wang LX (1999) A course in fuzzy systems and control. Prentice-Hall Press, USA, Ch. 14, pp. 180–183Google Scholar
  23. 23.
    Wang M, Zhang T, Liu C, Goto S (2009) Region-of-interest based dynamical parameter allocation for H. 264/AVC encoder. In: Picture Coding Symposium, 2009. PCS 2009, pp. 1–4Google Scholar
  24. 24.
    Winkler S, Sharma A, McNally D (2001) Perceptual video quality and blockiness metrics for multimedia streaming applications. In: Proc. International Symposium on Wireless Personal Multimedia Communications, Aalborg, pp. 547–552Google Scholar
  25. 25.
    Xu L, Li SN, Ngan KN, Ma L (2013) Consistent visual quality control in video coding. IEEE Trans Circuits Syst Video Technol 23:975–989Google Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Department of Electrical & Computer EngineeringUniversity of Sistan and BluchestanZahedanIran
  2. 2.Signal Processing Lab, Faculty of Electrical and Computer EngineeringUniversity of Sistan and BluchestanZahedanIran

Personalised recommendations