A Strategy of Distinguishing Texture Feature for Reversible Data Hiding Based on Histogram Shifting

Yinyin Peng, Zhao-Xia Yin

Abstract: Reversible data hiding has received growing attention, which not only protects the secret information but also can recover the cover image accurately. Many algorithms have aimed at embedding capacity and rarely consider the texture features of spatial images. In this paper, to better improve the image quality, a novel strategy of distinguishing texture feature for reversible data hiding based on histogram shifting is proposed. Firstly, the cover image is separated into blocks of the equal size, and the texture feature value of blocks is calculated. Then, the relatively smooth blocks are selected for information embedding. Experimental results show that our method can improve image quality effectively.