Abstract: Reversible data hiding (RDH) embeds a piece of information into a host signal to generate a marked one, so that the original signal is exactly recovered after the extraction of embedded data. For the images obtained with poor illumination, visual quality is more important than high PSNR value. The DH algorithm keeps the PSNR value high and enhances the contrast of the host image to improve the visual quality. The highest two bins in the histogram of the input image are shifted for data embedding, such that histogram equalization can also performed simultaneously by repeating the embedding process. The original image is completely recoverable by embedding side information along with the message bits to form a host image. Evaluation of images is an important step after data hiding, for determining how much the contrast has been enhanced. Quality of image is usually assessed using image quality metrics relative contrast error (RCE), relative entropy error (REE), relative mean brightness error (RMBE), relative structural similarity (RSS), peak signal to noise ratio (PSNR) and global contrast factor (GCF). This paper is a study of the various quantitative metrics for evaluating contrast enhancement. The results sho
Keywords: Reversible data hiding, Contrast Enhancement, Histogram binning, Steganography.