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

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A Correction to this article was published on 14 October 2017

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Abstract

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.

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  • 14 October 2017

    In the original publication, the affiliations of the two authors were incorrectly written as “University of Sistan and Bluchestan” when it should be “University of Sistan and Baluchestan.” The correct affiliations are presented in this erratum.

References

  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 20:806–819

    Article  Google Scholar 

  2. Chen Z, Liu H (2014) JND modeling: approaches and applications. Digital Signal Processing (DSP), 2014 19th International Conference on, 20–23 Auguest

  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 6:143–156

    Article  Google Scholar 

  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, September

  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. 1–4

  6. Lakshman T, Ortega A, Reibman AR (1998) VBR video: tradeoffs and potentials. Proc IEEE 86:952–973

    Article  Google Scholar 

  7. Liu H, Chen Z (2015) Exploiting perceptual redundancy in images. Visual Information Processing and Communication VI, SPIE Proceedings, Vol. 9410

  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 18:134–139

    Article  Google Scholar 

  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):935–948

    Article  Google Scholar 

  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):766–782

    Article  Google Scholar 

  11. Netravali AN, Prasada B (1977) Adaptive quantization of picture signals using spatial masking. Proc IEEE 65(4):536–548

    Article  Google Scholar 

  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. 65–70

  13. Reed EC, Dufaux F (2001) Constrained bit-rate control for very low bit-rate streaming-video applications. IEEE Trans Circuits Syst Video Technol 11:882–889

    Article  Google Scholar 

  14. Rezaei M, Hannuksela MM, Gabbouj M (2008) Semi-fuzzy rate controller for variable bit rate video. IEEE Trans Circuits Syst Video Technol 18:633–645

    Article  Google Scholar 

  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. 843–846

  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 September

  17. T. M. E. Committee (1993) MPEG-2 test model 5, Rev. 2, Section 10: Rate Control and Quantization Optimization, ISO/IEC/JTC1SC29WG11, April

  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. 942–945

  19. Tang C-W (2007) Spatiotemporal visual considerations for video coding. IEEE Trans Multimedia 9:231–238

    Article  Google Scholar 

  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 8:11–18

    Article  Google Scholar 

  21. Wandell BA (1995) Foundations of vision. Sinauer Associates, Sunderland

  22. Wang LX (1999) A course in fuzzy systems and control. Prentice-Hall Press, USA, Ch. 14, pp. 180–183

  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. 1–4

  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. 547–552

  25. Xu L, Li SN, Ngan KN, Ma L (2013) Consistent visual quality control in video coding. IEEE Trans Circuits Syst Video Technol 23:975–989

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Correspondence to Mehdi Rezaei.

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A correction to this article is available online at https://doi.org/10.1007/s11042-017-5274-9.

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Rezaei, M., Karimghasemi, E. A fuzzy rate controller for variable bit rate video using foveated just-noticeable distortion model. Multimed Tools Appl 76, 1439–1453 (2017). https://doi.org/10.1007/s11042-015-3110-7

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  • DOI: https://doi.org/10.1007/s11042-015-3110-7

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