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High-Dimensional Histogram Utilization for Reversible Data Hiding

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Book cover Digital-Forensics and Watermarking (IWDW 2014)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 9023))

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Abstract

Histogram-shifting (HS) is an efficient technique for reversible data hiding (RDH). In this paper, in contrast to previous HS-based RDH works that utilize one or two dimensional histogram, we propose a new RDH scheme exploring three-dimensional histogram. Referred to the recently proposed general framework of HS-based RDH, we first divide the host image into non-overlapping pixel triples to generate a three-dimensional histogram, and then utilize each triple for embedding or shifting based on an applicable triple classification. To further exploit the image redundancy to enhance the embedding performance, we apply the pixel-selection technique in our scheme such that smooth pixel triples are priorly embedded. Experimental results have verified the superiority of the proposed scheme over some state-of-the-art RDH works.

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Acknowledgement

The authors would like to thank Dr. Chuan Qin of University of Shanghai for Science and Technology (Shanghai 200093, China) and Dr. Ying-Hsuan Huang of National Chung Hsing University (Taichung 40227, Taiwan), for providing us the experimental results of their work [32].

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Authors and Affiliations

  1. Institute of Computer Science and Technology, Peking University, Beijing, 100871, China

    Xinlu Gui, Xiaolong Li & Bin Yang

Authors
  1. Xinlu Gui
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  2. Xiaolong Li
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  3. Bin Yang
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Corresponding author

Correspondence to Bin Yang .

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Editors and Affiliations

  1. NJIT, Newark, New Jersey, USA

    Yun-Qing Shi

  2. Korea University, Seoul, Korea, Republic of (South Korea)

    Hyoung Joong Kim

  3. Universidad de La Laguna, La Laguna, Spain

    Fernando Pérez-González

  4. Department of Computer Science and Information Engineering, National Dong Hwa University, Hualien, Taiwan

    Ching-Nung Yang

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Gui, X., Li, X., Yang, B. (2015). High-Dimensional Histogram Utilization for Reversible Data Hiding. In: Shi, YQ., Kim, H., Pérez-González, F., Yang, CN. (eds) Digital-Forensics and Watermarking. IWDW 2014. Lecture Notes in Computer Science(), vol 9023. Springer, Cham. https://doi.org/10.1007/978-3-319-19321-2_18

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  • DOI: https://doi.org/10.1007/978-3-319-19321-2_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19320-5

  • Online ISBN: 978-3-319-19321-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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