RDH (Reversible Data Hiding) in Encrypted Images by Reserving Room Before Encryption

RDH (Reversible Data Hiding) in Encrypted Images by Reserving Room Before Encryption
Authors:DURGA S PATIL, DR.SUDHIR S KANADE

Abstract: Now a day, more attention is to reversible data hiding (RDH) in encrypted images as well as in audio and video, by using RDH method excellent property that the original image (cover) can be receives as it is recovered after embedded data is extracted also protecting the image content’s confidentiality. All previous methods embedding data into image by reversibly vacating room in the encrypted images, which may be result as some errors on data extraction and/or image restoration. That mean some secrete information is loss in data extraction also degraded quality of image. In this paper, we propose a new method by reserving room before encryption .By using the new RHD method improver’s efficiency of image. The proposed method improves efficiency & quality encrypted image usually used in medical area, aromatic etc. The new Algorithm Used in novel RDH is reducing noise Effect. 

Keywords: Reversible Data Hiding, Image Encryption, Novel Method Of RDH, Encryption Techniques, Difference Expansion, Histogram Shift.

INTRODUCTION 

          Reversible data hiding (RDH) is a technique in image processing area for encryption, by which the original cover can be losslessly recovered after the embedded message, is extracted. The RDH approach is widely used in medical science, defense field and forensic lab, where there is no degradation of the original content is allowed. Since more research RDH method in recently. In theoretical aspect ratedistortion model for RDH Kalker and Willems [2], through which they proved the rate-distortion bounds of RDH for memory less covers and proposed a recursive code construction which, however, does not approach the bound. The recursive code construction for binary covers and proved that this construction can achieve the rate-distortion bound as long as the compression algorithm reaches entropy, which establishes the equivalence between data compression and RDH for binary covers. Many RDH techniques have emerged in recent years. Fridrich et al [3] constructed a general framework for RDH for method. By first extracting compressible features of original cover and then compressing them lossless, spare space can be saved for embedding auxiliary data.  

                                                                               Read More....