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UEP Network Coding for SVC Streaming

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Advances in Multimedia Information Processing -- PCM 2015 (PCM 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9315))

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Abstract

In this paper, we propose an optimized unequal error protection (UEP) network coding for scalable video coding (SVC). First, we introduce packet-level UEP network coding schemes which encode packets with different selection probabilities according to the priorities of video layers. Secondly, we explain how to prioritize the packet selection probability using distortion degree. The distortion degree accounts for the layers as well as group of pictures (GOP). Finally, experiment results demonstrate the performance of our proposed UEP network coding compared to other existing network coding methods in terms of decoding probability and peak signal to noise ratio (PSNR).

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Acknowledgement

This research was funded by the MSIP (Ministry of Science, ICT & Future Planning), Korea in the ICT R&D Program 2015.

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Authors and Affiliations

  1. School of Electronic and Electrical Engineering, Sungkyunkwan University, 2066, Seobu-ro, Jangan-gu, Suwon, 440-746, Korea

    Seongyeon Kim, Yong-woo Lee & Jitae Shin

Authors
  1. Seongyeon Kim
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  2. Yong-woo Lee
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  3. Jitae Shin
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Corresponding author

Correspondence to Jitae Shin .

Editor information

Editors and Affiliations

  1. Gwangju Institute of Science and Technology, Gwangju, Korea (Republic of)

    Yo-Sung Ho

  2. Chinese Academy of Sciences, Institute of Automation, Beijing, China

    Jitao Sang

  3. KAIST, Daejeon, Korea (Republic of)

    Yong Man Ro

  4. KAIST, Daejeon, Korea (Republic of)

    Junmo Kim

  5. College of Computer Science, Zhejiang University, Hangzhou, China

    Fei Wu

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© 2015 Springer International Publishing Switzerland

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Kim, S., Lee, Yw., Shin, J. (2015). UEP Network Coding for SVC Streaming. In: Ho, YS., Sang, J., Ro, Y., Kim, J., Wu, F. (eds) Advances in Multimedia Information Processing -- PCM 2015. PCM 2015. Lecture Notes in Computer Science(), vol 9315. Springer, Cham. https://doi.org/10.1007/978-3-319-24078-7_67

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  • DOI: https://doi.org/10.1007/978-3-319-24078-7_67

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24077-0

  • Online ISBN: 978-3-319-24078-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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