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Chinese Conference on Trusted Computing and Information Security

CTCIS 2017: Trusted Computing and Information Security pp 53–65Cite as

Double-Layered Predictor for High-Fidelity Reversible Data Hiding

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 704))

Abstract

The high-fidelity reversible data hiding aims to reduce the embedding distortion as far as possible, especially when the embedding capacity is low. To improve the embedding performance, a novel high-fidelity reversible data hiding method based on double-layered predictor is proposed. At first, the cover image is divided into two sets. The one set is used to predict the pixels in the other set according to the rhombus prediction method. Then, the prediction errors are used to embed data using pixel value ordering method. At last, the marked pixels in the first set are used to implement the process of embedding in the other set. To the best of our knowledge, the proposed predictor is the first double-layered predictor in the field of reversible data hiding. Extensive experiments demonstrate that the proposed method can significantly improve the embedding performance of the existing high-fidelity reversible data hiding method methods, especially for the relatively smooth images.

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Acknowledgments

This work is partially supported by National Natural Science Foundation of China (No. 6137915261403417 and 61402530), Shaanxi Provincial Natural Science Foundation (2014JQ8301).

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Authors and Affiliations

  1. Department of Electronic Technology, Engineering University of Chinese Peoples Armed Police, Xi’an, China

    Fuqiang Di, Junyi Duan, Jia Liu, Guangwei Su & Yingnan Zhang

Authors
  1. Fuqiang Di
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  2. Junyi Duan
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  3. Jia Liu
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  4. Guangwei Su
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  5. Yingnan Zhang
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Corresponding author

Correspondence to Jia Liu .

Editor information

Editors and Affiliations

  1. National University of Defense Technology, Changsha, China

    Ming Xu

  2. Hunan University, Changsha, Hunan, China

    Zheng Qin

  3. Wuhan University, Wuhan, China

    Fei Yan

  4. National University of Defense Technology, Changsha, Hunan, China

    Shaojing Fu

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Di, F., Duan, J., Liu, J., Su, G., Zhang, Y. (2017). Double-Layered Predictor for High-Fidelity Reversible Data Hiding. In: Xu, M., Qin, Z., Yan, F., Fu, S. (eds) Trusted Computing and Information Security. CTCIS 2017. Communications in Computer and Information Science, vol 704. Springer, Singapore. https://doi.org/10.1007/978-981-10-7080-8_5

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  • DOI: https://doi.org/10.1007/978-981-10-7080-8_5

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-7079-2

  • Online ISBN: 978-981-10-7080-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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