Reversible Data Hiding with Contrast Enhancement Based on Laplacian Image Sharpening

Abstract

In 2014, Wu et al. proposed a reversible data hiding method with contrast enhancement (RDH-CE) that emphasized that the visual quality of the image was more important than having a high peak signal-to-noise ratio (PSNR). But this method focused only on global enhancements and ignored the details. There were more obvious distortions of the visual image as the embedding level increased, and embedding capacity was relatively low when the embedding level was small. Therefore, in this paper, we proposed a new RDH method with contrast enhancement based on Laplacian sharpening. First, the details of the edges of images and the clarity of images were emphasized by Laplacian sharpening, and the visual distortions of the images were reduced by sharpening scale factor. Then, the embedding capacity was increased by combining the difference expansion and digital inverse transformation to apply the operator to all of the pixels in the image. The experimental results demonstrate the effectiveness of the proposed scheme.