Reversible Data Hiding With Image Enhancement Project 2022

Abstract-Traditional reversible data hiding (RDH) focuses on enlarging the embedding payloads while minimizing the distortion with a criterion of mean square error (MSE). Since imperceptibility can also be achieved via image processing, we propose a novel method of RDH with contrast enhancement (RDH-CE) using histogram shifting. Instead of minimizing the MSE, the proposed method generates marked images with good quality with the sense of structural similarity. The proposed method contains two parts: the baseline embedding and the extensive embedding. In the baseline part, we first merge the least significant bins to reserve spare bins and then embed additional data by a histogram shifting approach using arithmetic encoding. During histogram shifting, we propose to construct the transfer matrix by maximizing the entropy of the histogram. After embedding, the marked image containing additional data has a larger contrast than the original image. In the extensive embedding part, we further propose to concatenate the baseline embedding with an MSE-based embedding. On the recipient side, the additional data can be extracted exactly, and the original image can be recovered losslessly. Comparing with existing RDH-CE approaches, the proposed method can achieve a better embedding payload.