Skip to main content

Pixel-Copy Prediction Based Lossless Reference Frame Compression

  • Conference paper
  • First Online:
Advances in Multimedia Information Processing – PCM 2018 (PCM 2018)

Abstract

With the increasing demands of high definition and high resolution for video applications, the bandwidth and power consumption of accessing external memory storing reference frames during motion estimation bring serious pressure on practical video coding systems. Lossless reference frame compression is a proper method to decrease memory size and access bandwidth without any quality loss. This paper proposed a pixel-copy prediction based lossless reference frame compression. The method predicts current pixel by copying adjacent reconstructed pixels adaptively based on the estimations of the differences between the original pixel and the left and upper reconstructed samples. Then residuals are encoded by Huffman encoding to generate bit stream. Realized with HEVC reference software HM-16.5, experimental results show that our method achieves averagely 67.45\(\%\) data reduction ratio (DRR) for luminance component that outperforms pervious works on computation complexity and compression efficiency.

This work was supported by a grant from National Natural Science Foundation of China (NSFC, No. 61504032).

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Lin, C.C., Chen, J.W., Chang, H.C.: A 160K gates/4.5 KB SRAM H.264 video decoder for HDTV applications. IEEE J. Solid State Circuits 42(1), 170–182 (2006)

    Article  Google Scholar 

  2. Budagavi, M., Zhou, M.: Video coding using compressed reference frames. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 1165–1168. IEEE, Las Vegas, USA (2008)

    Google Scholar 

  3. Tuan, J.C., Chang, T.S., Jen, C.W.: On the data resuse and memory bandwidth analysis for full-search block-matching VLSI architecture. IEEE Trans. Circuits Syst. Video Technol. 12(1), 61–72 (2002)

    Article  Google Scholar 

  4. Li, D.X., Zheng, W., Zhang, M.: Architecture design for H.264/AVC integer motion estimation with minimum memory bandwidth. IEEE Trans. Consum. Electron. 53(3), 1053–1060 (2007)

    Article  Google Scholar 

  5. Chen, C.Y., Huang, C.T., Chen, Y.H.: Level C+ data reuse scheme for motion estimation with corresponding coding orders. IEEE Trans. Circuits Syst. Video Technol. 16(4), 553–558 (2006)

    Article  Google Scholar 

  6. Said, A., Pearlman, W.A.: A new, fast, and efficient image codec based on set partitioning in hierarchical trees. IEEE Trans. Circuits Syst. Video Technol. 6(3), 243–250 (1996)

    Article  Google Scholar 

  7. Song, L., Zhou, D.J., Jin, X., et al.: An adaptive bandwidth reduction scheme for video coding. In: IEEE International Symposium on Circuits and Systems (ISCAS), pp. 401–404. IEEE, Paris, France (2010)

    Google Scholar 

  8. Lin, C.-L.: A low latency coding scheme for compressing reference frame in video codec. In: 2017 International Conference on Applied System Innovation (ICASI), pp. 1957–1960. IEEE, Sapporo, Japan (2017)

    Google Scholar 

  9. Ma, Z., Segall, A.: Frame buffer compression for low-power video coding. In: IEEE International Conference on Image Processing (ICIP), pp. 757–760. IEEE, Brussels, Belgium (2011)

    Google Scholar 

  10. Kim, J., Kyung, C.M.: A lossless embedded compression algorithm for high definition video coding. In: IEEE International Conference on Multimedia and Expo, pp. 193–196. IEEE, New York, USA (2009)

    Google Scholar 

  11. Guo, L., Zhou, D.J., Goto, S.: Lossless embedded compression using multi-mode DPCM & averaging prediction for HEVC-like video codec. In: Proceedings of the 21st European Signal Processing Conference (EUSIPCO), pp. 1–5. IEEE, Marrakech, Morocco (2013)

    Google Scholar 

  12. Cheng, C.C., Tseng, P.C., Chen, L.G.: Multimode embedded compression codec engine for power-aware video coding system. IEEE Trans. Circuits Syst. Video Technol. 19(2), 141–150 (2009)

    Article  Google Scholar 

  13. Silveira, D., Povala, G., Amaral, L., et al.: Memory bandwidth reduction for H.264 and HEVC encoders using lossless reference frame coding. In: IEEE International Symposium on Circuits and Systems (ISCAS), pp. 2624–2627. IEEE, Melbourne VIC, Australis (2014)

    Google Scholar 

  14. Silveira, D., Povala, G., Amaral, L., et al.: A new differential and lossless reference frame variable-length coder: an approach for high definition video coders. In: IEEE International Conference on Image Processing (ICIP), pp. 5641–5645, France, Paris (2014)

    Google Scholar 

  15. Silveira, D., Povala, G., Amaral, L. et al.: Efficient reference frame compression scheme for video coding systems: algorithm and VLSI design. J. R. Time Image Process., 1–21 (2015)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jinxiang Wang .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Xu, W., Fu, F., Lou, B., Wang, Y., Wang, J. (2018). Pixel-Copy Prediction Based Lossless Reference Frame Compression. In: Hong, R., Cheng, WH., Yamasaki, T., Wang, M., Ngo, CW. (eds) Advances in Multimedia Information Processing – PCM 2018. PCM 2018. Lecture Notes in Computer Science(), vol 11165. Springer, Cham. https://doi.org/10.1007/978-3-030-00767-6_46

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-00767-6_46

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00766-9

  • Online ISBN: 978-3-030-00767-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics