Reversible data hiding based on histogram shifting of prediction errors using two predictors

Abstract

Reversible data hiding (RDH) is a special class of steganography that can not only embed secret data into images, but also can restore the original images after secret data are extracted. Prediction-based techniques constitute an important class of reversible data hiding methods. However, most prediction-based RDH rely on the use of a single predictor to compute predictions that are used for data embedding. This may restrict the embedding capacity and image quality. The objective of this paper is to improve the efficiency of prediction-based reversible data hiding algorithms by proposing an algorithm that employs multiple predictors to take advantage of their varying characteristics and prediction accuracy in order to increase the embedding capacity. The proposed algorithm is based on the efficient modification of prediction errors (MPE) algorithm; however, it incorporates two predictors and uses only one bin of the prediction errors histogram for data embedding. The performance evaluation of the proposed algorithm showed its ability to increase the embedding capacity with competitive image quality without the need for additional overhead information.