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

Abstract

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.