High-Capacity Reversible Data Hiding in Encrypted Images Based on Pixel Prediction and QuadTree Decomposition

Abstract

Over the past few years, a considerable number of researchers have shown great interest in reversible data hiding for encrypted images (RDHEI). One popular category among various RDHEI methods is the reserving room before encryption (RRBE) approach, which leverages data redundancy in the original image before encryption to create space for data hiding and to achieve high embedding rates (ERs). This paper introduces an RRBE-based RDHEI method that employs pixel prediction, quadtree decomposition, and bit plane reordering to provide high embedding capacity and error-free reversibility. Initially, the content owner predicts the error image using a prediction method, followed by mapping it to a new error image with positive pixel values and a compressed binary label map is generated for overhead pixels. Subsequently, quadtree decomposition is applied to each bit plane of the mapped prediction error image to identify homogeneous blocks, which are then reordered to create room for data embedding. After generating the encrypted image with the encryption key, the data hider employs the data hiding key to embed the data based on the auxiliary information added to each embeddable bit plane’s beginning. Finally, the receiver is able to retrieve the secret message without any error, decrypt the image, and restore it without any loss or distortion. The experimental results demonstrate that the proposed RDHEI method achieves significantly higher ERs than previous competitors, with an average ER exceeding 3.6 bpp on the BOSSbase and BOWS-2 datasets.