Reversible data hiding using multi-pass pixel value ordering and prediction-error expansion

Pixel value ordering (PVO) prediction has become the most efficient method for high-fidelity reversible data hiding (RDH). In this approach, only the maximum and minimum of pixel block are predicted and modified to embed data and the preservation of pixel value order guarantees the reversibility. To achieve larger embedding capacity and superior performance, more blocks suitable for RDH are utilized in recent improved schemes. However, their performance is still unsatisfactory. In this paper, a novel RDH scheme is proposed by extending original PVO into multi-pass PVO embedding. Specially, the k largest or smallest pixels are taken as independent data bit carriers to fulfill k-pass PVO embedding. Although the pixel value order may change after data embedding, reversibility still can be guaranteed and image redundancy can be far better exploited. Moreover, embedding performance can be further enhanced by optimal combined embedding. Experimental results verify that the proposed scheme outperforms previous PVO-based schemes and some other state-of-the-art works.     

Reversible data hiding with automatic contrast enhancement using two-sided histogram expansion

Recently, reversible data hiding (RDH) has emerged into a new class of data hiding methods that enables exact retrieving of both embedded data and cover medium. In the present study, a novel automatic RDH method with contrast enhancement is proposed, in which the data is embedded through two-sided histogram expansion. Two-sided histogram shifting doubles the number of bits embedded at each iteration. Moreover, it preserves the mean brightness of the cover image and prevents it from over enhancement with less calculation. Experimental results on two sets of images show that the proposed method enhances the image contrast at an appropriate level without using a mean brightness controller during data embedding and provides higher information security compared to the existing RDH approaches.     

Reversal of pixel rotation: A reversible data hiding system towards cybersecurity in encrypted images

Due to privacy and security concerns, the researches of reversible data hiding in encrypted images (RDHEI) have become increasingly important. Conventional schemes vacate the spare room after image encryption (VRAE) suffer from the low embedding rate, high error rate of data extraction, and imperfect image recovery. To address these issues, we propose a separable reversible data hiding scheme for encrypted images that utilizes a novel pixel rotation technique to embed data into fully encrypted images. The block complexities of four decrypted rotation states are considered when recovering image. To realize perfect image recovery, we further devise a lossless version (LPR-RDHEI). Experimental results demonstrate that the proposed PR-RDHEI scheme achieves an embedding rate of 0.4994 bpp on average and ensures lossless data extraction. Meanwhile, the proposed LPR-RDHEI scheme still has a 0.4494 bpp embedding rate on average. The embedding rates of our two schemes are significantly improved compared with state-of-the-arts.     

Reversible data hiding with contrast enhancement using adaptive histogram shifting and pixel value ordering

Existing image-based reversible data hiding (RDH) methods tend to focus on increasing embedding capacity, but few consider keeping or improving visual image quality. Wu et al. proposed a new RDH method with contrast enhancement (RDH-CE) by pair-wisely expanding the histogram to the lower end and upper end. RDH-CE is especially valuable in exploiting the details of poorly illustrated images for which the visibility of image details is more important than just keeping PSNR high. However, obvious visual image distortion appears when embedding level gets high, and embedding capacity is relatively low when embedding level is small. In this paper, Wu et al.'s work is improved from three perspectives, namely image contrast enhancement, visual distortion reduction, and embedding capacity increment. The image contrast is improved by making the histogram shifting process adaptive to the histogram distribution characteristics, the image visual distortion is reduced by cutting off half the modification range of pixels induced in histogram pre-shifting, and the embedding capacity is increased by exploiting the pixel value ordering technique at the early stage of data embedment. Experimental result proves that the proposed work is effective in improving image contrast, reducing visual image distortion, and increasing embedding capacity.     

Reversible data hiding based on multilevel histogram modification and pixel value grouping

This paper proposes a multilevel histogram modification based reversible data hiding scheme using a new difference generation strategy called pixel value grouping (PVG). It aims to produce shaper difference histogram by exploiting the high correlation among pixels within block. After sorting, pixel values are grouped according to their distribution. For each set of similar pixel values, real or virtual reference pixel will be determined to compute differences in the scope of pixel values group and next secret message is embedded through expansion embedding. By PVG, we success to greatly reduce the number of to-be-shifted pixels while producing sufficient EC and hence less distortion can be introduced for embedding the same payload. Moreover, the same grouping can be achieved at the decoder and the real or virtual reference pixel can be determined without any prior knowledge, which guarantees the reversibility. Experimental results demonstrate that our scheme outperforms previous related state-of-the-art schemes.     

Reversible data hiding in encrypted images with separability and high embedding capacity

In this paper, a high-capacity reversible data hiding (RDH) scheme for encrypted images with separability is proposed. The image is first divided into non-overlapping blocks, and each block is encrypted with the same random value. The advantage is that the correlation between adjacent pixels can be preserved. Utilizing the preserved correlation, the prediction difference in encrypted domain is exactly the same as that of plaintext domain, so that the separability can be achieved. Without accessing the original image content, the data-hider can embed additional data into encrypted image through histogram shifting and difference expansion. At the receiving end, the embedded additional data and the original image can be recovered without any error in separable manner. Experimental results are presented to demonstrate the feasibility and efficiency of the proposed scheme.     

Reversible data hiding in encrypted color images using cross-channel correlations

In recent years, the increasing requirements in cloud storage and cloud computing have made it necessary to encrypt digital images for privacy protection. Meanwhile, many reversible data hiding (RDH) algorithms in the encrypted domain have been proposed. However, most of these algorithms are for gray-level images, and the intrinsic cross-channel correlations of color images cannot be utilized to improve the embedding capacity. In this paper, we propose a novel data hiding method for encrypted color images. In the encryption stage, the homomorphic property of encryption is achieved by basic modular addition. During the data hiding process, the cross-channel correlations between R, G and B channels are generated in encrypted domain, and data hiding is performed by the difference histogram shifting. Analysis and experiments demonstrate that the proposed method is secure and the RDH performance is superior.     

Reversible data hiding for encrypted signals by homomorphic encryption and signal energy transfer

Reversible data hiding for encrypted signals with prefect reconstruction of directly decrypted signals is introduced in this paper. Each unit in the original image is separated into three components by energy transfer equation, and each component is encrypted by Paillier homomorphic encryption. Additional bits are concealed into the encrypted image by manipulating the encrypted signals. Finally, the original image can be perfectly recovered when direct decryption is applied. The embedded bits are lossless extracted as well. Optimal visual quality and improved embedding rate are obtained by the proposed approach, since the value of the directly decrypted unit is the same as the original one. Experimental results and comparisons are demonstrated to illustrate the effectiveness and advantages of the proposed method. Moreover, the proposed method can be extended to deal with encoded multimedia, which further enriches the application scenarios.     

Efficient reversible data hiding in encrypted images

This paper proposes a novel scheme of reversible data hiding in encrypted images based on lossless compression of encrypted data. In encryption phase, a stream cipher is used to mask the original content. Then, a data hider compresses a part of encrypted data in the cipher-text image using LDPC code, and inserts the compressed data as well as the additional data into the part of encrypted data itself using efficient embedding method. Since the majority of encrypted data are kept unchanged, the quality of directly decrypted image is satisfactory. A receiver with the data-hiding key can successfully extract the additional data and the compressed data. By exploiting the compressed data and the side information provided by the unchanged data, the receiver can further recover the original plaintext image without any error. Experimental result shows that the proposed scheme significantly outperforms the previous approaches.     

High capacity reversible data hiding in encrypted images using SIBRW and GCC

In this paper, a reversible data hiding in encrypted images (RDHEI) method combining GCC (group classification encoding) and SIBRW containing sixteen image-based rearrangement ways is proposed to achieve high-capacity data embedding in encrypted images. Each way of SIBRW aims at bringing strongly-correlated bits of each higher bit-plane together by rearranging each higher bit-plane. For each higher bit-plane, the optimal way achieving the most concentrated aggregation performance is selected from SIBRW to rearrange this bit-plane, and then, GCC compresses the rearranged bit-plane in group-by-group manner. By making full use of strong-correlation between adjacent groups, GCC can compress not only consecutive several groups whose bits are valued 1 (or 0) but also a single group so that a large embedding space is provided. The encryption method including the bit-level XOR-encryption and scrambling operations enhances the security. The experimental results show that the proposed scheme can achieve large embedding capacity and high security.     

A general framework for reversible data hiding in encrypted images by reserving room before encryption

In this paper a general framework to adopt different predictors for reversible data hiding in the encrypted image is presented. Employing linear regression, we propose innovative predictors that contribute more significantly to accomplish more payload than conventional ones. Reserving room before encryption (RRBE) is designated in the proposed scheme making possible to attain high embedding capacity. In RRBE procedure, pre-processing is allowed before image encryption. In our scheme, pre-processing comprises of three main steps: computing prediction-errors, blocking and labeling of the errors. By blocking, we obviate the need for lossless compression to when a content owner is not enthusiastic. Lossless compression is employed in recent state of the art schemes to improve payload. We surpass the prior arts exploiting proper predictors, more efficient labeling procedure and blocking of the prediction-errors.     

Reversible data hiding in encrypted images based on absolute mean difference of multiple neighboring pixels

Recently, with the development of cloud computing, more and more secret data are stored in cloud. Reversible data hiding in encrypted images is a technique that makes contribution to cloud data management in privacy preserving and data security. In previous works, Zhang and Hong presented two reversible dada hiding methods in encrypted images, respectively. However, Zhang’s work neglected the pixels in the borders of image blocks, and Hong et al.’s research only considered two adjacent pixels of each pixel. In addition, their works only considered that all image blocks are embedded into additional data. In this paper, we propose a novel method of evaluating the complexity of image blocks, which considers multiple neighboring pixels according to the locations of different pixels. Furthermore, data embedding ratio is considered. Experiments show that this novel method can reduce average extracted-bit error rate when the block size is appropriate.