An Efficient Reversible Data Hiding Based on Prediction Error Expansion

Reversible data hiding (RDH) is an approach that facilitates data hiding in a way that both the secret data and cover media can be extracted and recovered in their untouched form. Various RDH schemes have been proposed that utilize pixel value ordering mechanisms for pixel prediction and utilize histogram shifting (HS) criteria for prediction error expansion to implant secret data. However, such schemes are inefficient when it comes to hiding large volumes of data. In this paper, we propose a novel and improved RDH technique that divides the image into two using a checkboard pattern. One part of the image exploits the pixels of another part for prediction and vice versa. Also, as a parameter of smoothness, a fluctuation value is calculated for each pixel to avoid embedding in unsmooth regions of the image. The scheme is efficient in terms of hiding larger capacities of data and better stego-image quality.