Generalized Reversible Data Hiding with Content-Adaptive Operation and Fast Histogram Shifting Optimization.

Limengnan Zhou,Hongyu Han,Hanzhou Wu

doi:10.3390/e23070917

Abstract

Reversible data hiding (RDH) has become a hot spot in recent years as it allows both the secret data and the raw host to be perfectly reconstructed, which is quite desirable in sensitive applications requiring no degradation of the host. A lot of RDH algorithms have been designed by a sophisticated empirical way. It is not easy to extend them to a general case, which, to a certain extent, may have limited their wide-range applicability. Therefore, it motivates us to revisit the conventional RDH algorithms and present a general framework of RDH in this paper. The proposed framework divides the system design of RDH at the data hider side into four important parts, i.e., binary-map generation, content prediction, content selection, and data embedding, so that the data hider can easily design and implement, as well as improve, an RDH system. For each part, we introduce content-adaptive techniques that can benefit the subsequent data-embedding procedure. We also analyze the relationships between these four parts and present different perspectives. In addition, we introduce a fast histogram shifting optimization (FastHiSO) algorithm for data embedding to keep the payload-distortion performance sufficient while reducing the computational complexity. Two RDH algorithms are presented to show the efficiency and applicability of the proposed framework. It is expected that the proposed framework can benefit the design of an RDH system, and the introduced techniques can be incorporated into the design of advanced RDH algorithms.

Highlights

Reversible data hiding (RDH) [1,2], called reversible watermarking (RW), is referred to as the art of embedding extra data, such as source information and authentication data, into a host signal by slightly modifying the host signal
To further show its efficiency, we provide some experimental results on special images
We present a framework for prediction-based RDH technologies by revisiting a part of reported works

Summary

Introduction

Reversible data hiding (RDH) [1,2], called reversible watermarking (RW), is referred to as the art of embedding extra data, such as source information and authentication data, into a host signal ( called cover) by slightly modifying the host signal. The embedded information and the original host signal can be fully reconstructed from the marked content by a legal receiver [3,4]. As RDH enables us to perfectly recover the original host content, it is quite desirable and helpful in some sensitive scenarios, such as medical image processing, remote sensing, and military communication. Methods [5,6] mainly use lossless compression (LC) techniques to substitute a part of the host with the compressed code of the substituted part and the secret message. Since the LC procedure is often applied to the noise-like component of the host, the introduced distortion due to data embedding can be kept low.

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