Bidirectional Histogram Shifting Based Reversible Watermarking using Odd-Even Histogram Technique

Abstract

A new reversible watermarking has been proposed, which involves histogram shifting modulation and takes care of the local specificities of the image content. These methods allows the user to restore exactly the original image from its watermarked version by removing the watermark and thus it becomes possible to update the watermark content with less distortion. In this bidirectional histogram shifting modulation both the payload and PSNR value will be high were we can embed the secret image with less distortion and error. By applying it to the image prediction-errors and by proposed inserts data in the textured areas, a classification process is used for identifying parts of the image that can be watermarked with most suited reversible modulation. This classification is based on a reference image derived from the image itself, a prediction of it which has the property of being invariant to watermark insertion. In that way the watermark embedder and the extractor remain synchronized for image extraction and reconstruction. Here we are going to use Odd-Even Histogram shifting method through which we can hide two images for watermarking and based on the type application the data may vary for example the data can be an image, text or binary values. The experiments conducted so far on some natural images and on medical images show that capacities smaller than 0.7 bpp here we can insert more data with lower distortion. In Bidirectional Histogram Shifting we are going to embed and extract two or more images were the PSNR value and the Payload will be high while comparing to the existing watermark.