A high capacity reversible data hiding scheme based on generalized prediction-error expansion and adaptive embedding

• A high capacity reversible image data hiding scheme is proposed.
• A generalization of PEE and an adaptive embedding strategy are utilized for data embedding.
• The proposed scheme can well exploit image redundancy to achieve a high capacity with limited distortion.
• The proposed scheme shows obvious advantage over some state-of-the-art works especially for high capacity.

In this paper, a high capacity reversible image data hiding scheme is proposed based on a generalization of prediction-error expansion (PEE) and an adaptive embedding strategy. For each pixel, its prediction value and complexity measurement are firstly computed according to its context. Then, a certain amount of data bits will be embedded into this pixel by the proposed generalized PEE. Here, the complexity measurement is partitioned into several levels, and the embedded data size is determined by the complexity level such that more bits will be embedded into a pixel located in a smoother region. The complexity level partition and the embedded data size of each level are adaptively chosen for the best performance with an advisable parameter selection strategy. In this way, the proposed scheme can well exploit image redundancy to achieve a high capacity with rather limited distortion. Experimental results show that the proposed scheme outperforms the conventional PEE and some state-of-the-art algorithms by improving both marked image quality and maximum embedding capacity.