Applied Sciences (Sep 2022)

A Reversible Data-Hiding Method with Prediction-Error Expansion in Compressible Encrypted Images

  • Ryota Motomura,
  • Shoko Imaizumi,
  • Hitoshi Kiya

DOI
https://doi.org/10.3390/app12199418
Journal volume & issue
Vol. 12, no. 19
p. 9418

Abstract

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This paper proposes a novel reversible data-hiding method in encrypted images to achieve both a high hiding capacity and good compression performance. The proposed method can also decrypt marked encrypted images without data extraction, so marked images containing a payload can be derived from marked encrypted images. A perceptual encryption algorithm proposed for an encryption-then-compression framework is used to generate compressible encrypted images. In addition, a predictor with high accuracy and a prediction-error expansion and histogram shifting method are used for data hiding. Consequently, the proposed method can compress marked encrypted images without loss using image coding standards and achieve a high hiding rate. Experimental results show the effectiveness of the method in terms of hiding capacity or marked-image quality and lossless compression efficiency.

Keywords