LAUSR

Reversible data hiding (RDH) is a hot research topic, and many related techniques are proposed, but only a few are devised for color images. Most current RDH schemes, including those for color images, follow a well-developed framework: histogram-based embedding, which consists of two main steps, i.e., prediction-error histogram (PEH) generation by a pixel predictor and PEH modification through exploring efficient reversible mappings. The reversible mappings employed in these RDH approaches for color images, on the other hand, are empirically designed ignoring the specific image content, resulting in limited embedding performance. To address this issue, a novel RDH method for color images based on adaptive mapping selection is proposed in this paper. First, to leverage high inter-channel correlation of color images, a three-dimensional (3D) PEH is generated. Then, an effective reversible mapping selection mechanism is proposed, in which 3D mappings are adjusted in an ordered iterative manner according to PEH frequency ranking so that the embedding performance is optimized. By the proposed approach, the optimal reversible mapping can be acquired with low computing complexity and better embedding performance, and its efficiency is experimentally validated in comparison to various state-of-the-art studies.