明文图像可逆信息隐藏综述

As a branch of hidden information, reversible data hiding (RDH) has been developed over three decades. The key character of RDH differentiation is the reversibility that can ensure the adequate recovery of both the original image and the hidden message. The applications of targeted occasions have been focused on, such as medical, judicial and military image processing. Currently, RDH community has derived an enormous number of algorithms, each of which entangles a specialty of the other discipline. It may torture the consistent study of primary learners as they cannot control the situation and then feel confused and frustrating. The brief guidance may be required to provide a unique pathway of RDH research. The initial works have put more emphasis on the classical algorithms and aim to awake them simplistic and friendly. The potentials for the future are summarized and new scientific issues are proposed to integrate the RDH with the realistic applications, such as night image processing for surveillance and reconnaissance, image fusion for remote transmission storage, etc. In this review, we aim to provide a straightforward and explicit guideline for the readers with no formal training of this topic. We illustrate the typical RDH algorithms designed for the common images, and explain their motivations of reversible data embedding and extraction. Enlightened by the early-age motivations, we look forward the future directions to strengthen the close cooperation between RDH and the other leading disciplines. The whole paper consists of three parts, i.e., the researches for BMP images which are suited to the uncompressed images, the researches for JPEG images which are suitable for the coding-to-compression domain, and the robust reversible research in which more requirements are considered in the algorithm design to make RDH applicable for the practical case. In the reference list, nearly 100 papers are recommended for the study of this field. Most of the works are published in the top journals and conferences, and the significant influences of originality and innovation have been verified by the high citation rates in the past years. It is found that the RDH society has evolved into the form of great varieties and quantities. RDH is preferred by the expert and primary researchers due to its concise mathematical definition, simple experimental implementation and subtle embedding optimization. Such a simple and clear character allows RDH be easier to form a connection with the various applications without causing obvious conflicts. It is beneficial for the further development to have more discussions about the theoretical generality for diverse medium and introduce new evaluation metrics to guide the RDH design consisted with the practical application requirements. The unique feature of RDH is that it can recover the initial status of image when a change has taken place. It verifies that the image itself has the ability of recovery. In fact, the image is a sort of semantic expression relying on the strong but complicated data correlations. The correlations indicate that the image elements are similar to some extent, and can recover themselves in theory. In the existing works, the designers tend to understand the correlations at first, and then exploit the redundant elements to make space for hiding secret message. In a word, the algorithms revolve around the idea of better understanding the image. Of course, that how to interpret the correlations depends on the human-defined metric. In the current works, we are used to taking the PSNR metric to interpret the image, and then explore the boundary within which the distortion is acceptable and the main semantic information is preserved. However, merely PSNR is not sufficient to interpret the diversity of images. More metrics for different cases are better choices for the development of new and novel algorithms. Generally speaking, the reversibility is acceptable not only for the sensitive fields but also the common ones. The long-term development is feasible if RDH can respond more arising practical demands.