Skip to main content
SpringerLink
Log in

New bufferless rate control for high efficiency video coding

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

As a crucial component of video compression, rate control regulates the encoding bitrates of compressed bitstreams to meet channel bandwidths while obtaining optimum encoding quality. In this research, we investigate rate control techniques for High Efficiency Video Coding (HEVC/H.265) and propose a new Proportional-Integral-Derivative (PID) based direct rate control algorithm for HEVC/H.265. The objective is to achieve accurate bitrate control for real-time networked video applications. Based on the PID control theory, the proposed algorithm first performs target bit allocation, and then directly controls actual compression bitrates to get close to target encoding bitrates. Different from conventional rate control approaches, a buffer is not adopted in the proposed rate control algorithm which naturally reduces encoding delay and improves real-time response. When compared with the rate control scheme adopted by HEVC/H.265 reference software, our algorithm achieves superior performance according to the experimental results. Specifically, our proposed algorithm improves rate control accuracy up to 23.43%, and achieves higher encoding quality up to 3.47 dB.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Ang KG, Chong G, Li Y (2005) PID control system analysis, design, and technology. IEEE Trans Control Syst Technol 13(4):559–576

    Article  Google Scholar 

  2. Bossen F (2012) Common test conditions and software reference configurations. San Jose, JCT-VC of ITU-T SG16 WP3 and ISO/IEC JTC1/SC29/WG11, JCT-VC H1100.

  3. Choi H, Nam J, Yoo J, Sim D, Bajiæ IV (2012) Rate control based on unified RQ model for HEVC, JCTVC-H0213, 8th JCTVC meeting. CA, USA, San Jose

    Google Scholar 

  4. Choi H, Nam J, Yoo J, Sim D, Bajiæ IV (2013) Pixel-Wise. Unified Rate-Quantization Model for Multi-Level Rate Control IEEE Journal of Selected Topics in Signal Processing 7(6):1112–1123

    Article  Google Scholar 

  5. Gao W, Kwong S, Yuan H, Wang X (2016) DCT coefficient distribution modeling and quality dependency analysis based frame-level bit allocation for HEVC. IEEE Trans Circuits Syst Video Tech 26(1):139–153

    Article  Google Scholar 

  6. Gao W, Kwong S, Jia Y (2017) Joint machine learning and game theory for rate control in high efficiency video coding. IEEE Trans Image Proc 26(12):6074–6089

    Article  MathSciNet  Google Scholar 

  7. Gao W, Kwong S, Jiang Q, Fong CK, Wong PHW, Yuen WYF (2019) Data-driven rate control for rate-distortion optimization in HEVC based on simplified effective initial QP learning. IEEE Trans on Broadcasting 65(1):94–108

    Article  Google Scholar 

  8. Hu J, Peng W, and Chung C (2018) Reinforcement learning for hevc/h.265 intra-frame rate control. Proceedings of 2018 IEEE International Symposium on Circuits and Systems (ISCAS).

  9. Huang T, Zhang RX, Zhou C, Sun L (2018) QARC: video quality aware rate control for real-time video streaming via deep reinforcement learning. Proceedings of ACM Multimedia Conference. https://doi.org/10.1145/3240508.3240545

  10. Kim IK, McCann K, et al. (2012) High efficiency video coding (HEVC) test model 8 encoder description. JCT-VC of ITU-T SG 16 and ISI/IEC JTC1/SC 29/WG 11, Stockholm, JCTVC-J1002.

  11. Li B, Li H, Li L, Zhang J (2014) λ domain rate control algorithm for high efficiency video coding. IEEE trans. Image Process 23(9):3841–3854

    Article  MathSciNet  Google Scholar 

  12. Li S, Xu M, Deng X, Wang Z (2015) Weight-based R-λ rate control for perceptual HEVC coding on conversational videos. Signal Proc.: Image Communication 38:127–140

    Google Scholar 

  13. Li S, Xu M, Wang Z, Sun X (2017) Optimal bit allocation for CTU level rate control in HEVC. IEEE Trans on Circuits and Systems for Video Tech 27(11):2409–2424

    Article  Google Scholar 

  14. Liu Z, Wang L, Li X, Ji X (2019) Optimize x265 rate control: an exploration of Lookahead in frame bit allocation and slice type decision. IEEE Trans Image Process 28(5):2558–2573

    Article  MathSciNet  Google Scholar 

  15. Sullivan GJ, Ohm J, Han WJ, Wiegand T (2012) Overview of the high efficiency video coding (HEVC) standard. IEEE Trans. on Circuits and Systems for Video Technology 22(12):1649–1668

    Article  Google Scholar 

  16. Sun Y, Ahmad I (2004) A robust and adaptive rate control algorithm for objects based video. IEEE Trans Circuits Syst Video Technol 14(10):1167–1182

    Article  Google Scholar 

  17. Sun Y, Feng Z, Ginnavaram RR (2015) A direct non-buffer rate control algorithm for real time video compression. Multimed Tools Appl 74(17):6623–6639

    Article  Google Scholar 

  18. Wang M, Ngan K, Li H (2015) An efficient frame-content based intra frame rate control for high efficiency video coding. IEEE Signal Proc Letters 22(7):896–900

    Article  Google Scholar 

  19. Wang M, Ngan K, Li H (2016) Low-delay rate control for consistent quality using distortion-based Lagrange multiplier. IEEE Trans Image Process 25(7):2943–2955

    Article  MathSciNet  Google Scholar 

  20. Zhou M, Wei X, Wang S, Kwong S, Fong CK, Wong PHW, Yuen WYF, Gao W (2019) SSIM-based global optimization for CTU-level rate control in HEVC. IEEE Trans on Multimedia 21(8):1921–1923

    Article  Google Scholar 

  21. Zhou M, Wei X, Kwong S, Jia W, Fang B (2020) Rate control method based on deep reinforcement learning for dynamic video sequences in HEVC. IEEE Trans. on Multimedia 23:1106–1121. https://doi.org/10.1109/TMM.2020.2992968

    Article  Google Scholar 

Download references

Acknowledgements

This work was partially supported by NASA EPSCoR Award (No. NNX13AD32A) and faculty sabbatical leave fund from University of Central Arkansas.

Author information

Authors and Affiliations

  1. Department of Computer Science, University of Central Arkansas, 201 Donaghey Ave., Conway, AR, 72035, USA

    Yu Sun, Reese Childers & Joseph Hilton

Authors
  1. Yu Sun
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Reese Childers
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Joseph Hilton
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yu Sun.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sun, Y., Childers, R. & Hilton, J. New bufferless rate control for high efficiency video coding. Multimed Tools Appl 80, 28761–28776 (2021). https://doi.org/10.1007/s11042-021-11055-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-021-11055-z

Keywords

Search

Navigation