Wavelet bit-plane based data hiding for compressed images

In this paper, a wavelet bit-plane based data hiding for compressed images is proposed. Image compression not only reduces storage but also benefits transmission. Currently, image encoders including JPEG2000, SPIHT, EZW, etc. also provide multi-stage encoding/decoding. In this paper, the bit-planes of DWT coefficients are selected to carry the secret image according to the multi-stage encoding. The hidden secret image can be extracted progressively from multi-stage decoded images.Experimental results showed that the secret image was embedded and extracted in multi-stage coded images. Furthermore, the structure of secret image could be identified in earlier decoding stages and then refined in later stages. Accordingly, the progressive secret revealing is achieved. In comparison with the other similar schemes, the proposed method achieves the better quality of stego-image than the other two when the hiding capacity is the same.     

Adaptive reversible data hiding scheme based on integer transform

In this paper, we present a new reversible data hiding algorithm based on integer transform and adaptive embedding. According to the image block type determined by the pre-estimated distortion, the parameter in integer transform is adaptively selected in different blocks. This allows embedding more data bits into smooth blocks while avoiding large distortion generated by noisy ones, and thus enables very high capacity with good image quality. For instance, by the proposed method, we can embed as high as 2.17 bits per pixel into Lena image with a reasonable PSNR of 20.71 dB. Experimental results demonstrate that the proposed method outperforms some state-of-the-art algorithms, especially for high capacity case.     

Reversible data hiding scheme for high dynamic range images based on multiple prediction error expansion

For sensitive areas that even the slight distortion in images is not tolerated, we propose a prediction error expansion-based reversible data hiding algorithm which can embed reversible watermark in high dynamic range (HDR) image with low distortion. On the one hand, considering unique floating-point storage format and perceptual characteristics of HDR image, the multiple carriers are generated with low distortion and various characteristics to improve the embedding capacity. On the other hand, multi-model predictor and multi-level embedding strength are adopted adaptively to realize multi-level reversible HDR image information hiding based on prediction error expansion. The experimental results show that the proposed algorithm has good invisibility by making full use of HDR image characteristics. Meanwhile, the multiple strategies of multiple carriers, multi-model predictor and multi-level embedding strength, which further improve the embedding capacity and security of the algorithm, can meet the needs of sensitive areas such as medical processing, judicial authentication, and so on.     

Encrypted signal-based reversible data hiding with public key cryptosystem

Encrypted image-based reversible data hiding (EIRDH) is a well-known method allowing that (1) the image provider gives the data hider an encrypted image, (2) the data hider embeds the secret message into it to generate the encrypted image with the embedded secret message to the receiver, and (3) finally the receiver can extract the message and recover the original image without encryption. In the literature, the data hider and image provider must be specific parties who know the shared key with the receiver in traditional encrypted image-based reversible data hiding. In this paper, we propose an encrypted signal-based reversible data hiding (ESRDH) with public key cryptosystem, not only for images. The proposed scheme is secure based on Paillier homomorphic encryption. Finally, the experimental results show that the proposed scheme has much payload and high signal quality.     

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.     

Controlling hiding capacity using image characteristics with a 2D-DE data hiding scheme

Reversible data hiding techniques have gained much attention during the last few years because of the losslessness requirements of critical applications in military and medical fields. Among the various reversible data hiding techniques, difference expansion (DE) technique is one of the most popular techniques. The most common thing between DE-based schemes is their dependence on one or more thresholds. The threshold is used in order to control the hiding capacity aiming at keeping high visual quality of the embedded image. However, there is no such automatic way to predict or determine those thresholds as they are usually predefined. In this paper, we study the possibility of utilizing image characteristics as thresholds with a block based two-dimensional difference expansion scheme (2D-DE). The experimental results show that a threshold based on standard deviation may be used to control the hiding capacity and this leads to enhance the visual quality.     

An efficient reversible data hiding scheme using prediction and optimal side information selection

In this paper, we present an efficient histogram shifting (HS) based reversible data hiding scheme for copyright protection of multimedia. Firstly, an improved HS based multi-layer embedding process for rhombus prediction is employed by introducing a control parameter to explore the correlation of prediction errors. A rate-distortion model for HS embedding is then developed for optimal side information selection, which is especially suitable for low payload reversible data hiding when only a single layer embedding is required. Finally, a modified location map is constructed to facilitate the compression of location map and further increase the embedding capacity. Compared with similar schemes, experimental results demonstrate the superior performance of the proposed scheme in the terms of embedding capacity and stego-image quality.     

基于复合预测误差差值和互补嵌入的可逆数据隐藏

提出一种基于分块复合预测的误差差值和互补嵌入的彩色图像可逆数据隐藏算法。利用色彩分量之间的相关性和预测误差之间的关系减小差值,以增加差值直方图的峰值。采用双重嵌入方法提高嵌入容量,两次嵌入过程中像素值沿相反的方向扩展,部分像素值扩展量相互抵消,在图像分块的基础上选择最佳的预测方式组合,以增加扩展量抵消的机会,从而减小二次嵌入时图像质量的下降幅度。实验结果表明,本文算法在保证图像质量的同时大幅提高嵌入容量,算法的整体性能比其它同类算法更高。     

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.     

A novel high-performance reversible data hiding scheme using SMVQ and improved locally adaptive coding method

Reversible data hiding is a method that not only embeds secret data but also reconstructs the original cover image without distortion after the confidential data are extracted. In this paper, we propose novel reversible data hiding scheme that can embed high capacity of secret bits and recover image after data extraction. Our proposed scheme depends on the locally adaptive coding scheme (LAC) as Chang&Nguyen’s scheme and SMVQ scheme. Experimental results show that the compression rate of our proposed scheme is 0.33 bpp on average. To embed secret bits we propose the normal-hiding scheme and the over-hiding scheme which have an average embedding rate of 2.01 bpi and 3.01 bpi, more than that of Chang&Nguyen’s scheme (1.36 bpi). The normal-hiding scheme and the over-hiding scheme also has high embedding efficiency of 0.28 and 0.36 on average, which are better than that of Chang&Kieu’s scheme (0.12), Chang&Nguyen’s scheme (0.18) and Chang&Nguyen’s scheme (0.16).     

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.     

Efficient PVO-based reversible data hiding using multistage blocking and prediction accuracy matrix

In recent years, pixel value ordering based reversible data hiding has become a hot research topic for its high-fidelity. In this approach, only the maximum and minimum of pixel block are predicted and modified to embed data and the preservation of pixel values order guarantees the reversibility. So far, the optimal block size can only be exhaustively searched until Wang et al. propose the dynamic blocking strategy which enables the combination of two various-sized blocks. By further dividing flat block into four sub-blocks to retain larger embedding capacity, dynamic blocking can employ less high complexity blocks for a given embedding capacity. However, the lack of host image dependent automatic block classification mechanism still exposes the fact that their work is far from efficient and comprehensive. In this paper, to address this drawback and to better exploit image redundancy, a really efficient and more comprehensive blocking strategy namely multistage blocking is proposed. High efficiency lies in prediction accuracy matrix based thresholds determination, which enables infinitely extended multistage blocking in theory. The superiority of the proposed scheme is also experimentally verified.     

基于分块最佳预测的可逆数据隐藏

为了提高嵌入算法的性 能,提出一种基于分块最佳预测和直方图平移的灰度图像可逆数据隐藏算法。根据嵌 入阈值,统计 每一图像块中4种预测方案的嵌入容量,选择最大容量对应的预测方案作为该图像块的最佳 预测方案。嵌 入算法充分利用像素值局部相关性,自适应地选择最佳预测方案,有效提高嵌入容量。实验 结果表明,本 文算法在保证图像质量的同时有效提高嵌入容量,算法的整体性能比其它同类算法更优。     

Improved joint reversible data hiding in encrypted images

This paper proposes an improved method of reversible data hiding in encrypted images (RDH-EI). Three parties constitute the proposed system: the image owner, the remote server and the recipient. To preserve privacy, an image owner encrypts the original image using a stream cipher algorithm and uploads the ciphertext to a remote server. On server side, a data-hider is allowed to embed additional message into the encrypted image using a swapping/shifting based algorithm. After downloading the marked encrypted image from the server and implementing the decryption, a recipient can extract the hidden messages and losslessly recover the original image. Experimental results show that the proposed method achieves a larger payload than the related works. Meanwhile, a limitation in the related works that few bits can be embedded into the encrypted medical images is also eliminated in the proposed method.     

High-capacity reversible data hiding in encrypted image based on specific encryption process

This paper proposes a novel reversible data hiding method in encrypted images based on specific encryption process. In the proposed specific encryption algorithm, the stream cipher and prediction error are combined to vacate room for data embedding. After that, a permutation operation is performed on the encrypted image to improve the security. In the embedding process, we can embed a large amount of secret data in the encrypted image by pixel value expansion because most of the pixel values are less than 128 by the specific encryption process. At the receiver end, the encrypted image can be recovered from the marked encrypted image without knowing the secret data. Therefore, even if the recipient only has the encryption key, the original image will be perfectly recovered. If the recipient only has the data-hiding key, the secret data will be extracted. And if the recipient has both keys, the original image and the secret data are both available. The proposed method achieves a higher embedding capacity than that of methods based on vacating room after encryption. It does not require the image owner to perform reversible data hiding techniques on the original image, which is more convenient than methods based on reserving room before encryption. Experimental results demonstrate that the proposed method outperforms other state-of-the-art methods.     

基于边缘检测和像素分类的可逆数据隐藏

为了提高嵌入算法的整体性能,提出一种基于边缘检测和像素分类的灰度图像可逆数据隐藏算法。算法按嵌入容量优先原则自适应地选择最佳阈值提取图像边缘,并根据边缘信息和指定的图像质量控制因子将像素分为平滑、弱边缘和强边缘像素3类。对平滑像素,通过增加嵌入强度的方法提高嵌入容量,预测误差直方图平移2位;对弱边缘像素,像素值最大修改量为1,从而保证图像含密质量;强边缘像素的像素值保持不变,进一步提高含密图像质量。实验结果表明,本文算法在保证图像质量的同时有效提高嵌入容量,算法的整体性能优于其它同类算法。     

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.     

High-fidelity reversible data hiding based on pixel-value-ordering and pairwise prediction-error expansion

Pixel-value-ordering (PVO) technique refers to the process of first ranking the pixels in a block and then modifying the maximum/minimum for reversible data hiding (RDH). This paper discusses the PVO embedding in two-dimensional (2D) space and utilizes the prediction-error pair within a block for data embedding. We focus on not only the exploitation of conventional PVO embedding but also its effective implementation in 2D form. The PVO embedding is extended into a 2D form by integrating the pairwise prediction-error expansion, and a reversible 2D mapping adapted to the special distribution of prediction-error pairs is proposed. Moreover, an adaptive mapping selection mechanism is proposed to treat separately rough and smooth prediction-error pairs to further optimize the embedding performance. Experimental results show that the proposed method outperforms the previous PVO-based methods.