Reversible data hiding based on improved rhombus predictor and prediction error expansion

Rhombus predictor is an effective technique to achieve prediction error expansion based reversible data hiding. Considering the correlation of adjacent pixels, it achieves high performance prediction of the central pixel with the help of its surrounding four pixels in a rhombus cell. However, for cells with large fluctuation, such correlation is rather weak, leading to poor accuracy of prediction. In this paper, we propose a reversible data hiding scheme based on improved rhombus predictor, which takes the lead to consider consistencies along horizontal, vertical and diagonal directions of the rhombus cell simultaneously so that pixels with higher consistency are employed together to make up the predictor. To reduce the prediction error once watermark hits are not fully embedded, we further present a corresponding fluctuation based sorting strategy. The experimental results show that, with the same amount of watermark bits embedded, the proposed scheme is able to achieve better performance comparing with the classic scheme and the state-of-the art.