High-Fidelity Reversible Image Watermarking Based on Effective Prediction Error-Pairs Modification

Abstract

In reversible watermarking for image authentication, less degradation of the marked image is always desirable. For minimum distortion, the pairwise prediction-error expansion (PEE) technique was recently proposed to modify errors jointly. Although its superiority over conventional PEE has been verified, its potential has not been fully exploited yet. In this paper, we focus on optimal modification and propose an enhanced pairwise PEE. First, it is observed in PVO-based pairwise PEE that the histogram peak varies with relative location when predicting the largest/smallest two pixels. Then, a more effective 2D mapping is proposed by content-dependently selecting the expansion bin after introducing spatial location into prediction. Next, the 2D mapping is further extended considering prediction in non-smooth region tends to produce errors with large magnitude. Finally, we also propose to flexibly define the spatial location to achieve content-dependent prediction and further enhancement. Experimental results demonstrate that the proposed scheme achieves better capacity-distortion trade-off and outperforms several state-of-the-art schemes.