Reversible Data Hiding using Histogram Shifting Technique?

In this paper reversible data hiding (RDH), the original cover can be lossless restored after the embedded information is extracted. However, in some applications, such as medical imagery, military imagery, and law forensics, no degradation of the original cover is allowed. Kalker and Willems established a rate?distortion model for RDH, in which they proved out the rate?distortion bound and proposed a recursive code construction. In our existing base paper, we improved the recursive construction to approach the rate?distortion bound. In this paper, we generalize the method in our existing paper using a decompression algorithm as the coding scheme for embedding data and prove that the generalized codes can reach the rate?distortion bound as long as the compression algorithm reaches entropy. By the proposed binary codes, and we improve three RDH schemes that use binary feature sequence as covers, i.e., an RS scheme for spatial images, and one scheme for JPEG images, and a pattern substitution scheme for binary images. The experimental result shows that the novel codes can significantly reduce the embedding distortion. Furthermore, by modifying the histogram shift (HS) manner, we also apply these coding methods to one scheme that uses HS, and showing that the proposed codes can be also exploited to develop integer-operation-based schemes.