Reversible data hiding based on prediction-error histogram shifting and EMD mechanism

This paper proposes a reversible data hiding scheme for gray-level images. The scheme exploits the similarity among adjacent pixels and uses the side-match predictors to obtain prediction-error histogram. Then secret bits are embedded by using histogram shifting method. To achieve high capacity, nonary Exploiting Modification Direction (EMD) algorithm and multi-layer embedding mechanism are used when embedding the secret bits. Additionally, we improve the method of preventing overflow and underflow problems which enhances the compression ability of location map. In the extraction process, we use the same predictors to generate the error histogram, then we can extract the secret bits and recover the original cover image. Experimental results show that our algorithm can achieve better performance compared with the previous related algorithms.     

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 automatic contrast enhancement using histogram expansion

A lot of Reversible Data Hiding (RDH) methods aim to generate a stego image infinitely approaches the original image while the quality of the original image is leaved out of consideration. Juxtaposed with a plain image, a contrast enhanced version always improves the user experience significantly. Reversible Data Hiding with Contrast Enhancement (RDHCE) enhances the stego image contrast combined with its payloads and enables the cover image to be regained accurately after the payloads have been extracted. This study presents a novel RDHCE method using histogram expansion. First, a new local histogram selecting strategy is proposed to improve the contrast of the whole image. Meanwhile, the global average brightness is used as a reference to determine the shifting direction of the local histogram to prevent the image from being over-enhanced. Moreover, the contrast can be improved adaptively when a reasonable number of data is embedded at the selected embedding points. Experimental results show that, with a given payload, the proposed method achieves better contrast and maintains good visual quality compared with state-of-the-arts.     

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.     

基于小波系数差值直方图平移的可逆数据隐藏

针对传统差值直方图平移算法嵌入容量偏低、多重嵌入时图像质量严重下降等缺陷,提出一种基于整数小波系数差值直方图平移的彩色图像可逆数据隐藏算法。利用色彩分量间的相关性和小波系数间的关系减小差值,使差值直方图更加紧凑、峰值更大。采用双重嵌入方法提高嵌入容量,两次嵌入的像素值扩展方向相反,使得部分像素扩展量相互抵消,像素扩展量...     

基于双直方图平移的彩色图像可逆数据隐藏

提出一种基于双直方图平移的彩色图像可逆数据隐藏算法.利用色彩分量间的相关性减小差值,使差值直方图更加紧凑、直方图的峰值更大.采用直接调整像素值的方法在差值中嵌人数据,由像素值的二次可调整性定位不可调整像素,并嵌入少量的标志信息代替定位图,从而提高嵌入容量.实验结果表明,本文算法在保证图像质量的同时大幅提高了嵌入容量,与...     

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.     

基于排序和直方图修改的可逆信息隐藏方法

提出一种基于排序的差值直方图修改的可逆信息隐藏方法。首先,对图像分块;然后,采用按灰度值大小排序后的中值作为参考点,并和其余像素点做差,以产生更多的相同的值,使其差值直方图更紧凑、直方图的峰值点更大;最后,采用基于直方图修改的方法在差值中进行隐藏。实验表明,该方法不仅可以实现可逆信息隐藏,隐藏效果更好,并且嵌入量更高。为了提高嵌入量,进行了多层信息嵌入,并且在嵌入层数不同时采用不同的分块方式,提高了隐藏效果。分析了实验结果。     

基于三直方图平移和互补嵌入的可逆信息隐藏

为了提高嵌入算法的整体性能,提出一种基于三 差值直方图平移和互补嵌入的彩色 图像可逆信息 隐藏算法。利用色彩分量之间的相关性以及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 用三差值直方图平移和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方向扩展 ,部分像素值 扩展量相互抵消。选择两种不同的预测方向计算预测误差,以增加扩展量抵消的机会,解决 双重嵌入时图 像质量严重下降的难点问题。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.     

PVO-based reversible data hiding using adaptive multiple histogram generation and modification

A recently proposed pixel-value-ordering (PVO)–based reversible data hiding (RDH) method takes a sharp histogram derived from two skewed histograms, which realizes good performance through reducing the number of shifted pixels. However, in this recent work, since pixels with different local complexity are processed with the same modification manner based on a single histogram without considering their different local properties, the embedding performance is far from optimal. In this paper, to better exploit the pixel complexity and enhance the reversible embedding performance, a novel PVO-based RDH method using adaptive multiple histogram generation and modification is proposed. First, pixels with different local complexity are divided into several classes utilizing multiple thresholds. Then, a PVO-based predictor is used for prediction and multiple prediction-error histograms corresponding to the different pixel classes are obtained. Next, the generated histograms are modified to embed data according to their statistical characteristics. Here, based on the established capacity–distortion model, the histogram generation and modification are processed in an adaptive way to optimize the embedding performance. Moreover, by extending the proposed method to multiple two-dimensional prediction-error histograms, the embedding performance can be further improved. Experimental results verify that the proposed method outperforms certain state-of-the-art techniques with good marked-image quality.     

Reversible data embedding for indices based on histogram analysis

Reversible data hiding is a technique that not only protects the hidden secrets but also recovers the cover media without any distortion after the secret data have been extracted. In this paper, a new reversible data hiding technique for VQ indices which are compressed streams based on the mapping function and histogram analysis of transformed VQ indices is introduced to enhance the performance of some earlier reversible data hiding schemes that are based on VQ indices. As a result, the proposed scheme achieves high embedding capacity and data compression simultaneously. Moreover, the original VQ-compressed image can be perfectly reconstructed after secret data extraction. To estimate the performance of the proposed scheme, variety of test images are used in the experimental testing. As can be seen in the experimental result, our scheme is superior to some previous schemes in term of compression rate and embedding rate while maintaining the reversibility.     

High capacity multi-bit data hiding based on modified histogram shifting technique

A novel data hiding technique based on modified histogram shifting that incorporates multi-bit secret data hiding is proposed. The proposed technique divides the image pixel values into embeddable and nonembeddable pixel values. Embeddable pixel values are those that are within a specified limit interval surrounding the peak value of an image. The limit interval is calculated from the number of secret bits to be embedded into each embeddable pixel value. The embedded secret bits can be perfectly extracted from the stego image at the receiver side without any overhead bits. From the simulation, it is found that the proposed technique produces a better quality stego image compared to other data hiding techniques, for the same embedding rate. Since the proposed technique only embeds the secret bits in a limited number of pixel values, the change in the visual quality of the stego image is negligible when compared to other data hiding techniques.     

Reversible data hiding based on multiple histograms modification and deep neural networks

In the previous multiple histograms modification (MHM) based reversible data hiding (RDH) method, the prediction-error histograms are generated by a fixed manner, which may constrain the performance owing to the lack of adaptivity. In order to compensate this, we propose a deep neural networks (DNN) based method for dynamical multiple histograms generation. Through learning the prior knowledge, DNN is able to establish the histograms with different sizes for a better redundancy exploitation. For each histogram, two optimal expansion bins will be determined to minimize the distortion caused by the modification. Besides, the strategy consisted of the memo technique and the entropy measurement are applied to accelerate the parameter optimization. Experimental results show that the proposed method outperforms some of state-of-the-art RDH methods.     

High-capacity reversible data hiding in encrypted image based on Huffman coding and differences of high nibbles of pixels

In this paper, we propose a new reversible data hiding method in encrypted images. Due to spatial correlation, there is a large probability that the adjacent pixels of the image have small differences, which is especially obvious on the high four most significant bits (high nibbles) of the pixels. If the high nibble of each pixel is regarded as a 4-bit value, the differences between the high nibbles of the adjacent pixels are mostly concentrated in a small range. Based on this fact, Huffman coding was used to encode all the differences between the high nibbles of the adjacent pixels in order to compress the four most significant bit (MSB) planes efficiently and create a large-capacity room. After creating room, a stream cipher is used to encrypt the image, and the room is reserved in the encrypted image for data hiding without losing information. The experimental results showed that the proposed method can achieve a larger embedding rate and better visual quality of the marked decrypted image than other related methods.     

基于插值预测和块分类的低失真可逆数据隐藏

提出一种基于插值预测和块分类模型的低失真可 逆数据隐藏算法。首先,对原始图像 进行插值预测, 得到预测误差图像;然后根据误差图像建立直方图,使得产生的直方图更陡峭,峰值点出现 频率更大;接 着对误差图像进行分块,利用块分类模型,在隐藏块内利用直方图平移隐藏信息,尽可能地 减少平移点的 数量;最后,相应地修改原始像素的灰度值,得到低失真的隐秘图像。实验结果表明,本文 算法不仅可以实现可逆数据隐藏,而且隐藏效果较好,有效载荷较高。     

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。     

基于互补嵌入的彩色图像可逆数据隐藏

针对传统差值直方图平移算法嵌入容量偏低、多重嵌入时图像质量严重下降等缺陷,提出一种基于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整数小波系数之间的关系减小差值,以增加差值直方图的峰值。采用双重直方图平移方法提高嵌入容量,两次嵌入过程的像素值扩展方向相反,部分像素值扩展量相互抵消,扩展量最大值为1。实...     

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).