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International Conference on Cloud Computing and Security

ICCCS 2016: Cloud Computing and Security pp 48–62Cite as

Reversible Data Hiding with Low Bit-Rate Growth in H.264/AVC Compressed Video by Adaptive Hybrid Coding

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10039))

Abstract

For the reversible data hiding algorithm in compressed-domain videos, secret data embedding process usually lead to a large bit-rate growth of video stream, thus the imperceptibility and security will be decreased. In order to solve this problem, a reversible data hiding algorithm with low bit-rate growth in H.264/AVC compressed video by adaptive hybrid coding is proposed in this paper. In the proposed scheme, the hybrid coding algorithm has been adaptively applied on different trailing coefficients, which makes the algorithm have a considerable embedding capacity and a low bit-rate growth. Compared with the existing reversible data hiding algorithm for video, the proposed scheme has a lower bit-rate growth with the same hiding capacity.

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Acknowledgments

This work is supported by the National Natural Science Foundation of China (U1536110).

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Authors and Affiliations

  1. School of Information Science and Technology, Southwest Jiaotong University, Chengdu, 611756, China

    Tian-Qi Wang, Hong-Xia Wang & Yue Li

Authors
  1. Tian-Qi Wang
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  2. Hong-Xia Wang
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  3. Yue Li
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Corresponding author

Correspondence to Tian-Qi Wang .

Editor information

Editors and Affiliations

  1. University of Information Science and Technology, Nanjing, China

    Xingming Sun

  2. Michigan State University , EAST LANSING, Michigan, USA

    Alex Liu

  3. National Dong Hwa University , Shoufeng, Taiwan

    Han-Chieh Chao

  4. Purdue University , West Lafayette, Indiana, USA

    Elisa Bertino

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© 2016 Springer International Publishing AG

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Cite this paper

Wang, TQ., Wang, HX., Li, Y. (2016). Reversible Data Hiding with Low Bit-Rate Growth in H.264/AVC Compressed Video by Adaptive Hybrid Coding. In: Sun, X., Liu, A., Chao, HC., Bertino, E. (eds) Cloud Computing and Security. ICCCS 2016. Lecture Notes in Computer Science(), vol 10039. Springer, Cham. https://doi.org/10.1007/978-3-319-48671-0_5

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  • DOI: https://doi.org/10.1007/978-3-319-48671-0_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-48670-3

  • Online ISBN: 978-3-319-48671-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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