Skip to main content
SpringerLink
Log in

A Wyner-Ziv Video Coding method utilizing mixture correlation noise model

  • Published:
Journal of Electronics (China)

Abstract

In Wyner-Ziv (WZ) Distributed Video Coding (DVC), correlation noise model is often used to describe the error distribution between WZ frame and the side information. The accuracy of the model can influence the performance of the video coder directly. A mixture correlation noise model in Discrete Cosine Transform (DCT) domain for WZ video coding is established in this paper. Different correlation noise estimation method is used for direct current and alternating current coefficients. Parameter estimation method based on expectation maximization algorithm is used to estimate the Laplace distribution center of direct current frequency band and Mixture Laplace-Uniform Distribution Model (MLUDM) is established for alternating current coefficients. Experimental results suggest that the proposed mixture correlation noise model can describe the heavy tail and sudden change of the noise accurately at high rate and make significant improvement on the coding efficiency compared with the noise model presented by DIStributed COding for Video sERvices (DISCOVER).

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

Similar content being viewed by others

References

  1. Bernd Girod, Anne Aaron, Shantanu Rane, et al.. Distributed video coding. Proceedings of the IEEE, 93(2005)1, 71–83.

    Article  Google Scholar 

  2. Frederic Dufaux, Wen Gao, Stefano Tubaro, et al.. Distributed video coding: trends and perspectives. EURASIP Journal on Image and Video Processing, 2009, 508167, DOI:10.1155/2009/508167.

  3. Li-wei Kang and Chun-Shien Lu. Distributed compressive video sensing, International Conference on Acoustics, Speech and Signal Processing, Taipei, China, April 2009, 1169–1172.

  4. Anne Aaron, Rui Zhang, and Bernd Girod. Wyner-Ziv coding of motion video. Proceedings of Asilomar Conference on Signals and Systems, Pacific Grove, CA, USA, November 2002, 240–244.

  5. DISCOVER Page. http://www.discoverdvc.org, December 2007.

  6. Jürgen Slowack, Jozef Škorupa, Stefaan Mys, et al.. Correlation noise estimation in distributed video coding. Effective Video Coding for Multimedia Applications. Intech Publishing, Rijeka, Croatia, 2011, 133–156.

  7. Jürgen Slowack, Jozef Škorupa, Stefaan Mys, et al.. Exploiting quantization and spatial correlation in virtual-noise modeling for distributed video coding. Signal Processing: Image Communication, 25(2010)9, 674–686.

    Article  Google Scholar 

  8. Xin Huang and Søren Forchhammer. Cross-band noise model refinement for transform domain Wyner-Ziv video coding. Signal Processing: Image Communication, 27(2012)1, 16–30.

    Article  Google Scholar 

  9. Catarina Brites and Fernando Pereira. Correlation noise modeling for efficient pixel and transform domain Wyner-Ziv video coding. IEEE Transactions on Circuits and Systems for Video Technology, 18(2008)9, 1177–1190.

    Article  Google Scholar 

  10. Thomas Maugey, Jerome Gauthier, Beatrice Pesquet-Popescu, et al.. Using an exponential power model for Wyner Ziv video coding. IEEE International Conference on Acoustics Speech and Signal Processing, Dallas, TX, March 2010, 2338–2341.

  11. Fang Sheng, Li Zhe, Liang Yongquan, et al.. Research of the virtual dependency channel in distributed video coding. Journal of Computers, 32(2009)7, 1404–1412 (in Chinese). 房胜, 李哲, 梁永全, 等. 分布式视频编码虚拟依赖信道模型研究. 计算机学报, 32(2009)7, 1404–1412.

    Google Scholar 

  12. Wang Fengqin, Fan Yangyu, Zhao Jiong, et al.. Correlation noise model for transform domain Wyner-Ziv video coding. Journal of Data Acquisition & Processing, 24(2009)5, 609–614 (in Chinese). 王凤琴, 樊养余, 赵炯, 等. 基于变换域Wyner-Ziv视频编码的相关噪声模型. 数据采集与处理, 24(2009)5, 609–614.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Image Processing and Image Communication Key Laboratory, Nanjing University of Posts and Telecommunications, Nanjing, 210003, China

    Xiaofei Hu & Xiuchang Zhu

  2. College of Geography and Biological Information, Nanjing University of Posts and Telecommunications, Nanjing, 210003, China

    Xiaofei Hu

Authors
  1. Xiaofei Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiuchang Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Xiaofei Hu.

Additional information

Supported by the National Natural Science Foundation of China (No. 61071091) and Jiangsu Province Graduate Innovative Research Plan (CX07B_107Z).

Communication author: Hu Xiaofei, born in 1975, female, Associate Professor, Ph.D. candidate.

About this article

Cite this article

Hu, X., Zhu, X. A Wyner-Ziv Video Coding method utilizing mixture correlation noise model. J. Electron.(China) 29, 197–203 (2012). https://doi.org/10.1007/s11767-012-0815-x

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11767-012-0815-x

Key words

CLC index

Search

Navigation