Minimum Rate Prediction and Optimized Histograms Modification for Reversible Data Hiding

Abstract

Prediction-error expansion (PEE)-based reversible data hiding schemes consist of two steps. First, a sharp prediction-error (PE) histogram is generated by utilizing pixel prediction strategies. Second, secret messages are reversibly embedded into the prediction-errors through expanding and shifting the PE histogram. Previous PEE methods treat the two steps independently while they either focus on pixel prediction to obtain a sharp PE histogram, or aim at histogram modification to enhance the embedding performance for a given PE histogram. This paper propose a pixel prediction method based on the minimum rate criterion for reversible data hiding, which establishes the consistency between the two steps in essence. And correspondingly, a novel optimized histograms modification scheme is presented to approximate the optimal embedding performance on the generated PE sequence. Experiments demonstrate that the proposed method outperforms the previous state-of-art counterparts significantly in terms of both the prediction accuracy and the final embedding performance.