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Reversible Data Hiding Based on Combined Predictor and Prediction Error Expansion

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Digital-Forensics and Watermarking (IWDW 2014)

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

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Abstract

This paper presents a novel reversible data hiding method which uses a combined predictor. The proposed combined predictor combines five base predictors according to their global and local predicting performance. The weights to combine the base predictors are calculated with a pixel by pixel manner that they adjust to the local image patch characteristics. The proposed predictor is shown to have high prediction precision which is beneficial for the following prediction error expansion (PEE). Observing that our predictor performs well even for images with complex textures, a novel pixel selection criterion that bases on the prediction errors is proposed, which can accurately select the pixels that have small prediction errors to use. Extensive experiments are conducted to verify the superior performance of the proposed method.

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Acknowledgments

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (No. 2012015587), and the National Natural Science Foundation of China (no. 61173147).

Author information

Authors and Affiliations

  1. Graduate School of Information Security and Management, Korea University, Seoul, 136-701, Korea

    Xiaochao Qu, Suah Kim, Run Cui & Hyoung Joong Kim

  2. School of Information Science and Technology, Sun Yat-Sen University, Guangdong, 510-006, China

    Fangjun Huang

Authors
  1. Xiaochao Qu
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  2. Suah Kim
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  3. Run Cui
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  4. Fangjun Huang
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  5. Hyoung Joong Kim
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Corresponding author

Correspondence to Hyoung Joong Kim .

Editor information

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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© 2015 Springer International Publishing Switzerland

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Qu, X., Kim, S., Cui, R., Huang, F., Kim, H.J. (2015). Reversible Data Hiding Based on Combined Predictor and Prediction Error Expansion. 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_19

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  • DOI: https://doi.org/10.1007/978-3-319-19321-2_19

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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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