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Histogram shifting based reversible data hiding method using directed-prediction scheme

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Abstract

This paper aims at reducing the shifting distortion of histogram shifting reversible data hiding method. Instead of calculating symmetrically the prediction value as were done in other schemes, based on the gradient-adjusted predictor (GAP), a directed-prediction scheme, which includes two asymmetric predictors-the right and left GAPs, is designed to predict asymmetrically pixel value. Then two asymmetric error histograms, with right and left-skewness, are constructed by gathering the directed prediction errors, which effectively reduces the amount of pixels on the shifted side of the error histograms. Moreover, the optimal embedding points and thresholds are calculated by defining an evaluation index of the shifting distortion. Experimental results validate the effectiveness of the proposed method and demonstrate that it outperforms several previous methods in terms of payload and image quality.

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Acknowledgments

This work is supported by the National Natural Science Foundation of China (No. 61232016, 61173141, 61173142, 61173136, 61103215, 61373132 and 61373133), GYHY201206033, 2013DFG12860, 201301030, BC2013012 and Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD fund).

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Authors and Affiliations

  1. School of Information Science and Engineering, Hunan University, Hunan, 410082, China

    Xianyi Chen, Xingming Sun, Lingyun Xiang & Bin Yang

  2. Jiangsu Engineering Center of Network Monitoring, Nanjing University of Information Science and Technology, Nanjing, 210044, China

    Xingming Sun

  3. Department of Mathematical Sciences, University of Bath, Bath, BA2 7AY, UK

    Huiyu Sun

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  1. Xianyi Chen
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  2. Xingming Sun
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  3. Huiyu Sun
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  4. Lingyun Xiang
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  5. Bin Yang
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Correspondence to Xingming Sun.

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Chen, X., Sun, X., Sun, H. et al. Histogram shifting based reversible data hiding method using directed-prediction scheme. Multimed Tools Appl 74, 5747–5765 (2015). https://doi.org/10.1007/s11042-014-1881-x

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  • DOI: https://doi.org/10.1007/s11042-014-1881-x

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