A high capacity data hiding scheme for binary images based on block patterns

This paper proposes a high capacity data hiding scheme for binary images based on block patterns, which can facilitate the authentication and annotation of scanned images. The scheme proposes block patterns for a 2 × 2 block to enforce specific block-based relationship in order to embed a significant amount of data without causing noticeable artifacts. In addition, two kinds of matching pair (MP) methods, internal adjustment MP and external adjustment MP, are designed to decrease the embedding changes. Shuffling is applied before embedding to reduce the distortion and improve the security. Experimental results show that the proposed scheme gives a significantly improved embedding capacity than previous approaches in the same level of embedding distortion. We also analyze the perceptual impact and discuss the robustness and security issues.     

A novel data hiding scheme based on modulus function

Four criteria are generally used to evaluate the performance of data hiding scheme: the embedding capacity, the visual quality of the stego-image, the security, and the complexity of the data-embedding algorithm. However, data hiding schemes seldom take all these factors into consideration. This paper proposes a novel data hiding scheme that uses a simple modulus function to address all the performance criteria listed above. According to the input secret keys, the encoder and decoder use the same set-generation functions H_r() and H_c() to first generate two sets Kr and Kc. A variant Cartesian product is then created using Kr and Kc. Each cover pixel then forms a pixel group with its neighboring pixels by exploiting an efficient modulus function; the secret data are then embedded or extracted via a mapping process between the variant of the Cartesian product and each pixel group. The proposed scheme offers several advantages, namely (1) the embedding capacity can be scaled, (2) a good visual quality of the stego-image can be achieved, (3) the computational cost of embedding or extracting the secret data is low and requires little memory space, (4) secret keys are used to protect the secret data and (5) the problem of overflow or underflow does not occur, regardless of the nature of the cover pixels.We tested the performance of the proposed scheme by comparing it with Mielikainen’s and Zhang and Wang’s schemes for gray-scale images. The experimental results showed that our proposed scheme outperforms Mielikainen’s in three respects, namely scalable embedding capacity, embedding rate, and level of security. Our data hiding scheme also achieved a higher embedding capacity than Zhang and Wang’s. The proposed scheme can easily be applied to both gray-scale and color images. Analyses of its performance showed that our proposed scheme outperforms Tsai and Wang’s in terms of its time complexity and memory space requirement.     

A reversible data hiding scheme based on graph neighbourhood degree

Abstract

The perceptibility and capacity are two vital criteria of data hiding scheme. Concerning these criteria, data hiding algorithm used images as cover object based on the graph theory is proposed in this study. Images are quantised according to determined range and then quantised images are divided into n × n sized blocks. Each block is accepted as a graph and vertexes which have the same quantisation value are accepted as neighbours. Neighbourhood degrees of vertexes are calculated and indices of vertexes that have a neighbourhood degree over the threshold value are stored in the codebook. Pixel values indicated by these indices in the codebook are used for data hiding process. In this algorithm, there is no need for edge extraction because of hiding data to pixels containing vertexes having high neighbourhood degrees. The proposed method is compared with similar methods in literature in terms of the perceptibility and capacity. More successful results are provided than the others.     

Multilevel reversible data hiding based on histogram modification of difference images

Reversible data hiding has drawn considerable attention in recent years. Reversibility allows original media to be completely recovered from marked media without distortion after embedded message has been extracted. In this paper we propose a multilevel reversible data hiding scheme based on the difference image histogram modification that uses the peak point to hide messages. Through a joint imperceptibility and hiding capacity evaluation, we show that our proposed scheme uses a multilevel hiding strategy to achieve large hiding capacity and keep distortion low. Performance comparisons with other existing reversible hiding schemes are provided to demonstrate the validity of our proposed scheme.     

Data hiding in grayscale images by dynamic programming based on a human visual model

A new method for data hiding in grayscale images based on a human vision model with distortion-minimizing capabilities is proposed. Each of the eight bit planes of an input grayscale image is viewed as a binary image, into which message data are embedded horizontally. Two optimization techniques, namely, block pattern coding and dynamic programming, are proposed for image distortion minimization. Experimental results show good performs of the proposed method.     

基于分存的多幅图像信息隐藏方案*

在秘密图像分存的基础上,提出一种多幅图像进行信息隐藏的算法。首先把秘密图像分存到指定的两个毫无关系的图像中,然后在公开图像的奇数行（列）嵌入第一幅图像,在偶数行（列）嵌入第二幅图像,从而实现多幅图像在一幅公开图像中的隐藏。给出了两幅图像嵌入一幅图像的实验,并对隐藏性能作了分析与比较。该算法原理简单有效,编程容易,信息的嵌入与提取速度快,并且这种多幅图像进行信息隐藏的方法可以嵌套于目前的大多数算法,有很强的推广性。     

A reversible data hiding scheme based on the Sudoku technique

Data hiding, also known as information hiding, plays an important role in information security for various purposes. Reversible data hiding is a technique that allows distortion-free recovery of both the cover image and the secret information. In this paper, we propose a new, reversible data hiding scheme that is based on the Sudoku technique and can achieve higher embedding capacity. The proposed scheme allows embedding more secret bits into a pair of pixels while guaranteeing the good quality of the stego-image. The experimental results showed that the proposed scheme obtained higher embedding capacity than some other previous schemes. In addition, our proposed scheme maintained the good visual quality of the stego-image (i.e., PSNR > 46 dB), which outperforms some existing schemes.     

High capacity data hiding schemes for medical images based on difference expansion

Since the difference expansion (DE) technique was proposed, many researchers tried to, improve its performance in terms of hiding capacity and visual quality. In this paper, a new scheme, based on DE is proposed in order to increase the hiding capacity for medical images. One of the characteristics of medical images, among the other types of images, is the large smooth regions. Taking advantage of this characteristic, our scheme divides the image into two regions; smooth region and non-smooth region. For the smooth region, a high embedding capacity scheme is applied, while the original DE method is applied to the non-smooth region. Sixteen DICOM images of different modalities were used for testing the proposed schemes. The results showed that the proposed scheme has higher hiding capacity compared to the original schemes.     

An adaptive data hiding scheme with high embedding capacity and visual image quality based on SMVQ prediction through classification codebooks

This study exploits the characteristics of image blocks to develop an adaptive data hiding scheme that is based on SMVQ prediction. Since human beings’ eyes are highly sensitive to smooth images, changes in smooth cause great distortion and attract the attention of interceptors. Hence, this study proposes a data embedding scheme for embedding secret data into edge blocks and non-sufficiently smooth blocks. The experimental results show that the proposed scheme improves the quality of the stego-image and the embedding capacity.     

增强图像平滑度的可逆信息隐藏方案

随着互联网技术的发展和社交网络的普及,可逆信息隐藏技术因其具有无损恢复载体信息的特性而被广泛应用于医疗、军事等领域的隐蔽信息传输。传统的可逆信息隐藏方案大多聚焦于嵌入容量提升和载密图像失真率降低,并未过多关注人们对图像视觉细节的要求,难以抵抗隐藏信息检测方法。针对上述挑战,从增强图像视觉平滑度方面入手,提出了一种增强图像平滑度的可逆信息隐藏方案,在嵌入隐蔽信息的同时提升载密图像最终的视觉质量。具体来说,所提方案将目标图像分为参考区域与非参考区域,利用非参考区域的图像像素预测值与原始像素值的差值作为信息嵌入的判断依据,通过差值平移来嵌入信息;进而构造图像平滑机制,采用高斯滤波作为秘密信息嵌入时像素值修改的模板,对预测值进行滤波计算,将滤波差值无损地加入载体图像中,以达到图像平滑的效果;同时将参考区域的像素值作为边信息,用于实现信息提取方对原始载体图像和秘密信息的无损恢复和提取;并以高斯函数中的滤波系数作为预置秘密信息对嵌入信息进行加密处理以保证嵌入信息的机密性。大量经典图像数据集的测试与分析结果表明,所提方案处理过的载密图像视觉平滑度得到了显著增强,具有较低的失真率、较高的嵌入率和较高的嵌入提取效率。在典型环境下,其生成的载密图像与高斯滤波后的图像相似度可达0.996 3,且可获得37.346的峰值信噪比和0.328 9的嵌入容量。     

Hiding data in compressive sensed measurements: A conditionally reversible data hiding scheme for compressively sensed measurements

Most of the real-world signals we encounter in real-life applications have low information content. In other words, these signals can be well approximated by sparse signals in a proper basis. Compressive sensing framework uses this fact and attempts to represent signals by using far fewer measurements as compared to conventional acquisition systems. While the CS acquisition is linear, the reconstruction of the signal from its sparse samples is nonlinear and complex. The sparse nature of the signal allows enough room for some additional data sequence to be inserted and exactly recovered along with the reconstructed signal. In this study, we propose to linearly embed and hide data in compressively sensed signals and nonlinearly reconstruct both of them using a deflationary approach. We investigate the embedding capacity as a function of signal sparsity and signal compression, as well as the noise sensitivity of the proposed algorithm.     

基于位平面压缩的密文医学图像可逆信息隐藏算法

针对目前医学图像可逆信息隐藏算法嵌入容量小、需要对图像进行感兴趣区域（ROI）划分、接收方操作不灵活等缺点,结合医学图像特点,提出了一种基于位平面压缩的可分离式密文域信息隐藏算法。首先,将256级灰度医学图像分解成8个位平面,压缩高4个位平面,用峰值点像素值填充压缩后的空间,重构图像;然后,对重构的图像头部、中部、尾部分别加密;最后,在尾部根据嵌入密钥选取位置,通过直方图平移算法嵌入信息,接收方可根据密钥持有情况实现信息提取与图像恢复的可分离操作。实验结果表明,通过压缩图像预留空间来存放信息避免了辅助信息的传输,能有效提高嵌入容量,同时具有较高的安全性。     

图像空域可逆信息隐藏研究进展

可逆信息隐藏是信息隐藏技术的重要分支,它不仅能从含密载体中提取秘密信息,还能无损地还原原始载体。以图像空域为载体的可逆信息隐藏研究根据图像是否被加密可分为明文域和密文域。早期,该领域研究基本在明文域开展,在保证可逆嵌入的前提下,着重提高嵌入容量与减少嵌入失真。随着人们日益重视隐私保护和数据安全,密文域的信号处理引起广泛关注。密文域可逆信息隐藏结合加密技术和可逆信息隐藏技术,从而达到载体内容保护和秘密信息传递的双重目的。本文梳理现有的相关文献,分别对明文域和密文域的研究进行归纳与分析,按照时间先后顺序帮助理清各类方法的发展脉络及其关联。首先,概括明文域的经典方法,包括差值扩展、直方图平移、预测误差扩展和多直方图修改4种方法及其改进版本。其次,阐述密文域中基于加密后腾出空间、加密前预留空间和通过加密腾出空间3类方法的研究进展。再次,总结指出明文域的研究趋向于减少嵌入失真,而密文域的研究趋向于提高嵌入容量,其在鲁棒性及安全性方面的进展则相对缓慢。最后,结合当前研究面临的实际问题,如载体多元化、有损信道传输和安全性等,进一步展望未来的研究趋势。总之,可逆信息隐藏研究的有效性与实用性仍有待提高,面向不同应用需求时,亟需学者提出新的理论支撑与评价体系。     

基于纹理度划分的医学图像可逆信息隐藏方法

针对目前具有对比度增强效果的可逆信息隐藏（RDH）算法大多受到嵌入率的影响,未能实现较好的对比度增强效果的问题,提出一种基于纹理度划分的医学图像可逆信息隐藏方法。首先,通过对比度拉伸的方法实现医学图像对比度增强;然后,再利用医学图像纹理度的自身特点,将医学图像划分为高、低两类纹理度等级,其中高纹理度等级构成医学图像的关键部分;最后,为了进一步增强高纹理度等级的对比度并保证信息嵌入率,对不同的纹理度等级像素采用不同的嵌入方法。为了与其他具有对比度增强效果的医学图像可逆信息隐藏算法比较载密图像的对比度增强效果,采用了针对对比度失真的无参考图像质量评价标准（NR-CDIQA）作为实验客观依据。实验结果表明,在不同嵌入率下,使用所提方法的载密图像的NR-CDIQA值更高,对比度增强效果更好。     

基于差值直方图的简单高效可逆信息隐藏方法

提出一种基于图像相邻像素差值直方图的可逆信息隐藏方法,运用该方法同时提高了信息嵌入容量和嵌入信息后的图像质量。首先对原始图像进行分块、扫描并求取差值直方图,然后在分块图像的差值直方图中选取最高的两个峰值点并向两个方向移位来产生空缺用于信息嵌入。算法充分利用了自然图像的相邻相似特性,同时提高了基于直方图的信息隐藏方案的峰值点数目和峰值点高度,从而大大提高信息嵌入容量。此外,算法在信息嵌入前对待嵌入信息的预处理使得在嵌入同样容量的信息时,对载体图像的影响更小,具有更好的嵌入后图像质量。     

Data hiding based on compressed VQ indices of images

The VQ-based data hiding technique has not received much attention compared to various spatial domain-based data hiding techniques in digital images. Consequently, a new data hiding scheme, applied in the VQ-compressed domain of cover images, is introduced in this article. To provide more hiding capacity for secret data and to keep an acceptable bit rate for the compressed cover images, the search-order-coding (SOC) algorithm was implemented to compress the VQ indices of the cover images in the process of data hiding. During the process of data hiding, the proposed scheme embeds secret data into the compressed VQ indices of the cover image adaptively, adjusting the bit rate according to the size of the secret data and the compressed cover image. In addition, the hiding process induces no extra coding distortion. Experiments show that the receiver can efficiently receive both the secret data and the compressed cover image simultaneously with an acceptable bit rate. Simulation results also demonstrate that our proposed scheme outperforms earlier proposed methods.     

基于JPEG图像的模块化可逆信息隐藏方法

当前的可逆信息隐藏方法为了寻求更好的嵌入性能,通常会基于给定的图像内容对修改模式和嵌入参数作出自适应的调整。然而,通过细化自适应程度或扩大解空间来寻找更优解时,会造成计算复杂度高、时间成本难以承受等问题。为此,提出了一种适用于JPEG图像的模块化可逆嵌入方法来提高自适应寻优的效率。通过比较不同情况下最优解的嵌入性能,对原有的解空间进行优化、筛选,从而生成一个适用于不同图像的通用修改模式集合。每一个修改模式被定义为在多直方图修改框架下的最优嵌入点集合。在嵌入时,为给定的图像内容自适应地从预设的解集中选定合适的修改模式。实验在USC-SIPI数据集上与五个具有代表性的方法进行了比较。相比于同类算法,所提算法可将峰值信噪比提升0.03～1.81 dB。对于文件大小扩展,所提算法的性能结果可比两个经典方法分别减少12.4%和5.1%。实验结果表明,相比于主流经典方法,该方法在含密图像质量和文件大小扩展方面有更好的性能表现,并能以较低的计算复杂度取得与最近的高效方法相近的自适应嵌入效果。     

基于高阶位平面冗余的可逆信息隐藏方法

针对现有加密图像可逆信息隐藏(RDHEI)方法存在的隐藏容量低、解密标记图像质量差的问题,提出了一种新的基于高阶位平面冗余的RDHEI方法.首先,通过Logistic映射对原始图像进行分块加密,并保留块内像素高阶位平面的冗余;其次,依据块内高阶位和低阶位个数是否相同的规则将加密后的图像块分为可嵌入块和不可嵌入块,并在可...