A new reversible data hiding scheme exploiting high-dimensional prediction-error histogram

Pairwise prediction-error expansion (pairwise PEE) is an improvement of the conventional PEE and it can provide excellent performance for reversible data hiding (RDH). Unlike PEE in which the prediction-errors are modified individually, the correlation among prediction-errors is exploited in pairwise PEE by jointly modifying each prediction-error pair. In this paper, the idea of pairwise PEE is developed and a new RDH scheme is proposed. A three-dimensional prediction-error histogram (3D-PEH) is generated by counting every non-overlapped prediction-error triple. Then, data embedding is conducted by modifying the 3D-PEH with a specifically designed reversible mapping. By using 3D-PEH and the proposed reversible mapping, the inter-correlation of prediction-errors is better exploited, and the performance of PEE is significantly enhanced. Moreover, the superiority of our method over pairwise PEE and some other state-of-the-art RDH methods is also experimentally verified. The proposed method is an effective extension of PEE towards the direction of high-dimensional histogram modification.