Adaptive Predictor Structure Based Interpolation for Reversible Data Hiding

  • Sunil Prasad Jaiswal
  • Oscar Au
  • Vinit Jakhetiya
  • Andy Yuanfang Guo
  • Anil K. Tiwari
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9023)


In this paper, we present an additive prediction error expansion (PEE) based reversible data hiding scheme that gives overall low distortion and relatively high embedding capacity. Recently reported interpolation based PEE method uses fixed order predictor that fails to exploit the correlation between the neighborhood pixels and the unknown pixel (to be interpolated). We observed that embedding capacity and distortion of PEE based algorithm depends on the prediction accuracy of the predictor. In view of this observation, we propose an interpolation based method that predicts pixels using predictors of different structure and order. Moreover, we use only original pixels for interpolation. Experimental results demonstrate that the proposed algorithm outperforms the state-of-the-art algorithms both in terms of embedding capacity and Peak Signal to Noise Ratio.


Reversible image watermarking Predictor order Embedding capacity Interpolation 


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Sunil Prasad Jaiswal
    • 1
  • Oscar Au
    • 1
  • Vinit Jakhetiya
    • 1
  • Andy Yuanfang Guo
    • 1
  • Anil K. Tiwari
    • 2
  1. 1.The Hong Kong University of Science and TechnologyKowloonHong Kong
  2. 2.Indian Institute of TechnologyRajasthanIndia

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