全数字全息术在图像信息隐藏中的应用

提出了全数字全息术在计算机图像信息隐藏中的应用。待隐藏的秘密信息以及公开的承载信息均为灰度级静止图像。首先对待隐藏的计算机信息图进行全息变换,即通过计算全息图的制作步骤制作出全息图的图像文件,然后再进行Arnold对称性变换。在此基础上,将秘密图像嵌入到承载图像的DCT域的中频系数中。全数字全息术的引入进一步增强了隐藏图像的透明性,通过控制制作全息图时的参数可起到加密的作用,相当于增加了一把秘密钥匙,具有较高的保密性和稳健性。     

基于数字全息及离散余弦变换的图像数字水印技术

提出了一种以数字全息和离散余弦变换为基础的数字水印技术,实现了在原始图像中嵌入数字全息水印。考虑到数字全息图的不可撕毁性,使得数字全息水印本身就具有良好的抗剪切能力,并且与传统的二维灰度水印相比嵌入的信息更多。数字全息图通过傅里叶变换全息的方法获得,为了提高抗有损压缩能力,在数字全息水印嵌入过程中采用了基于(JPEG模型和分解离散余弦变换(DCT)系数的方法。实验表明,通过该算法获得的数字全息水印对JPEG有损压缩和剪切等图像处理操作均有很好的稳健性,并且采用密钥加强了水印的安全性。因此该算法能成为数字多媒体产品版权保护的有效方案。     

提升小波变换和混沌加密的数字声频水印

提出了一种提升小波变换和混沌加密的数字声频水印算法.先对声频信号进行提升小波变换,通过修改提升小波变换系数的统计平均值来实现同步码和水印信息的嵌入,利用听觉掩蔽阈值来自适应确定最佳嵌入强度,以保证嵌入隐藏信息对人耳的不可感知性;为了改善水印的安全性,采用改进logistic混沌映射产生密钥序列对隐藏信息进行加密.实验结果表明:与传统的傅里叶变换、余弦变换、小波变换的声频水印方案相比,本文方法具有更好的不可感知性和安全性,且能够更加有效地抵抗各种常见信号处理攻击.     

基于双混沌置乱和扩频调制的彩色图像盲水印算法

提出了一种新的适应彩色图像的盲水印算法,先对宿主图像的绿色分量以8×8像素分块进行离散余弦变换(DCT)变换,用logistic映射生成两个混沌序列,然后用混沌序列置乱加密二值水印图像,并用两个互不相关的伪随机序列扩频调制水印,最后将调制好的水印嵌入到DCT变换域的中频子带系数上,进行分块DCT反变换得到水印化图像.提取水印时,通过比较两个伪随机序列和水印化图像的相关性大小来提取水印,不需要原始图像的参与,为盲提取水印算法.实验结果证明本文算法能有效地抵抗JPEG压缩、加噪、剪切等常见攻击,绿色分量嵌入水印比红色和蓝色分量嵌入水印能更好地抵抗JPEG压缩的攻击.     

基于分块DCT变换编码的小波域多幅图像融合算法

提出了一种利用DCT变换和小波变换的特征层图像融合算法.其基本思想是先对多幅源图像进行分块DCT变换,选取较大方差对应的变换系数,将图像压缩为原图像大小的1/4,保留系数的对应坐标作为提取信息时的密钥;其次将经处理后的DCT系数直接作为小波变换的分解系数,经小波逆变换后得到融合信息.实验结果表明,该算法实现了多幅不同大小图像的融合,同时单一密钥只能提取单一图像. 关键词： 图像融合 小波变换 离散余弦变换 编码     

基于分块离散小波变换的图像信息隐藏与盲提取算法

提出了一种在小波域中图像信息隐藏与盲提取算法. 该算法首先对载体图像进行分块两层离散小波变换, 找到每块第二级分解子带中的最大值即最重要小波系数, 然后根据小波特征树的对应关系将其在第一级分解子带中的对应区域作为嵌入区域, 在该区域嵌入由秘密信息生成的伪随机序列. 提取过程中, 同样按照小波系数对应关系寻找到嵌入区域并判断其与伪随机序列的相关性即可解密, 不需要提供原始图像. 实验结果表明, 该算法能实现二值图像的嵌入与盲提取, 且提取出的图像质量较好并具备一定的抗攻击能力, 尤其对于剪切攻击的鲁棒性较好.     

半色调编码计算全息图的数字水印方法

提出一种新的基于信息光学的数字水印方法。该方法将水印信息隐藏于半色调编码的计算全息图之中。通过相位复原技术将需隐藏的水印信息编码为相位函数嵌入在复波前中,其振幅定义为宿主图像,通过计算全息记录复波前并对全息图进行半色调编码完成水印信息的嵌入。水印的提取过程只需对含有水印信息的半色调图像进行光学或数字的傅里叶变换即可完成。并给出了算法有效性的理论分析和仿真实验结果。结果证明这种水印技术对于各种数字图像处理操作具有很高的稳健性,且半色调编码图的二值特性使嵌入水印具有很强的抗打印、抗复印、抗扫描的能力。     

基于HVS的小波域信息隐藏方法

为了提高信息隐藏的不可感知性和鲁棒性,结合人眼视觉系统(HVS)的相关知识,提出了一种新的小波域信息隐藏算法。将载体图像的中等亮度区域设为不可用区域,不在该区域隐藏信息,同时选择在载体图像小波变换的高频系数细节子图隐藏信息,并优先选择在对角高频系数细节子图中隐藏。计算局部子块的方差值作为隐藏信息的嵌入系数,并通过计算高频子图的噪声敏感模型ωθ(i,j)决定隐藏信息的位置。充分考虑了人眼的各种视觉掩蔽效应,使得隐藏信息后的结果图像相比隐藏之前没有出现明显的降质。实验结果表明该方法能够有效提高信息隐藏的不可知性,达到了很好的隐藏效果,同时能够有效地抗击噪声、裁剪和压缩等攻击影响,具有很好的鲁棒性,在信息安全领域有较好的应用前景。     

基于相移干涉术的光学信息隐藏系统的软件实现

结合双随机相位编码技术与相移干涉术，提出了一种信息隐藏系统，待隐藏信息被加密到多幅干涉图数据中后。通过选取合适的权重因子，它们可以被嵌入到宿主图像中；利用特定的相移再现公式和逆菲涅耳衍射变换，可以实现隐藏信息的提取及解密．通过基于Matcom的VisualC＋＋与Matlab混合编程，设计和开发了一款信息隐藏系统软件，经过界面测试，该软件可以实现图像读取及显示、基本几何参数输入、信息加密及嵌入、信息提取及解密、鲁棒性测试等主要功能．     

基于K-SVD和残差比的低信噪比图像稀疏表示去噪算法

针对低信噪比图像去噪问题,提出了一种基于K-SVD(Singular Value Decomposition)和残差比(Residual Ratio Iteration Termination)的正交匹配追踪(Orthogonal Matching Pursuit,OMP)图像稀疏分解去噪算法。该算法利用K-SVD算法将离散余弦变换(Discrete cosine transform,DCT)框架产生的冗余字典训练成能够有效反映图像结构特征的超完备字典,以实现图像的有效表示。然后以残差比作为OMP算法迭代的终止条件来实现图像的去噪。实验表明,该算法相对于传统基于Symlets小波图像去噪、基于Contourlet变换的图像去噪,以及基于DCT冗余字典的稀疏表示图像去噪,能够更加有效地滤除低信噪比图像中的高斯白噪声,保留原图像的有用信息。     

Optical color image hiding scheme by using Gerchberg–Saxton algorithm in fractional Fourier domain

We proposed an optical color image hiding algorithm based on Gerchberg–Saxton retrieval algorithm in fractional Fourier domain. The RGB components of the color image are converted into a scrambled image by using 3D Arnold transform before the hiding operation simultaneously and these changed images are regarded as the amplitude of fractional Fourier spectrum. Subsequently the unknown phase functions in fractional Fourier domain are calculated by the retrieval algorithm, in which the host RBG components are the part of amplitude of the input functions. The 3D Arnold transform is performed with different parameters to enhance the security of the hiding and extracting algorithm. Some numerical simulations are made to test the validity and capability of the proposed color hiding encryption algorithm.     

A novel data hiding and reversible scheme using SMN blocks in VQ-compressed images

Data hiding is a technique for embedding secret data into cover media. It is important to multimedia security and has been widely studied. Reversible data hiding methods are becoming prevalent in the area because they can reconstruct the original cover image while extracting the embedded data. In this paper, we propose a new reversible method for vector quantization (VQ) compressed images. Our method takes advantages of the relationship among the side match neighbouring (SMN) blocks to achieve reversibility. The experimental results show that the proposed method has higher compression rate and larger capacity than other existing reversible methods.     

Demosaicking authentication codes using adaptive step via color difference estimation

In this paper, data hiding is used for raw images instead of the full-resolution color version. Among various color filter array patterns, we choose the most popular Bayer pattern and cover authentication codes in the pseudo host from original sampling in terms of high correlation within red, blue and green channels. pseudo host is based on a transient image that is created by interpolating in this pattern by selecting the key. This procedure confirms the security, in the meantime, and less brings the artifact of embedding codes. This process exploits spatial correlations both red and blue channel to adaptively tune quantization scale parameter and suppresses visual distortion. Core structure presents a watermarking to jointly resist to demosaicking and JPEG compression approach. It can carry visual distortion as small as possible. The simulations test the robustness and transparency after some demosaicking methods and JPEG compression. These results imply that hiding data accompany with less demosaicking traces and the better robustness via various demosaicking methods.     

Steganalysis of HMPD reversible data hiding scheme

Based on feature mining and pattern classification, this paper presents a steganalysis technique against reversible data hiding by histogram modification of pixel differences scheme (HMPD). HMPD reversible data hiding scheme involves the modification of pixel differences, which introduces artifacts into the pixel-difference histograms. It is found that four-way pixel difference features are sensitive for HMPD embedding algorithm. These features are used to design a specific steganalysis method for detecting HMPD reversible data hiding scheme. Support Vector Machine (SVM) classifiers are trained to discriminate stego-images from cover images and estimate the secret keys of a stego image. The experimental results show that the proposed scheme not only successfully attacks HMPD reversible data hiding scheme in various embedding levels, but also accurately estimates the secret keys.     

一种基于Logistic混沌系统和奇异值分解的零水印算法

改变了传统通过修改图像内容进行版权保护的做法,描述了一种基于混沌理论和奇异值分解（singular value decomposing,SVD）的零水印方案;利用了Logistic混沌系统的初值敏感性映射信息隐藏的位置,增强了算法的安全性;采用了奇异值的不变特性构造注册中心的水印,保证了在不改变宿主图像任何信息的同时进行有效地版权保护;将有意义的二值图像作为水印图像,解决了零水印方案水印为无意义二值序列的问题;同时深入分析了水印容量和算法安全性之间的关系.通过对标准测试图像、卡通、医学、风景、遥感、诗画等 关键词： 零水印 混沌系统 Logistic系统 奇异值分解     

Adversarial Data Hiding in Digital Images

In recent studies of generative adversarial networks (GAN), researchers have attempted to combine adversarial perturbation with data hiding in order to protect the privacy and authenticity of the host image simultaneously. However, most of the studied approaches can only achieve adversarial perturbation through a visible watermark; the quality of the host image is low, and the concealment of data hiding cannot be achieved. In this work, we propose a true data hiding method with adversarial effect for generating high-quality covers. Based on GAN, the data hiding area is selected precisely by limiting the modification strength in order to preserve the fidelity of the image. We devise a genetic algorithm that can explore decision boundaries in an artificially constrained search space to improve the attack effect as well as construct aggressive covert adversarial samples by detecting “sensitive pixels” in ordinary samples to place discontinuous perturbations. The results reveal that the stego-image has good visual quality and attack effect. To the best of our knowledge, this is the first attempt to use covert data hiding to generate adversarial samples based on GAN.     

Fuzzy self-adaptive digital audio watermarking based on time-spread echo hiding

In this paper, a fuzzy self-adaptive digital audio watermarking method based on a time-spread echo hiding algorithm is proposed. Echo spreading is performed in the impulse response domain using PN sequences to achieve good robustness of echo hiding and high secrecy of spread spectrum. Fuzzy theory is employed in the embedding process to control the power of the watermark. Since fuzzy set theory is capable of performing complex nonlinear mappings between input and output spaces, it can effectively estimate the strength of a frame for each subband and ensure that the embedded watermark in the original audio is self-adaptive. A listening test and simulation results show that the algorithm is robust for common digital audio processing methods as attacks and that the quality of the audio is retained.     

Multiple-image hiding in the Fresnel domain

To avoid additive cross-talk among multiple images, they are separated from each other and even from the host image in the hiding and the extraction process by locating them independently in the Fresnel domain with computer-generated double phase-only masks. Gray images and white-ground and black-ground binary images can be hidden in the system at the same time. The hiding capacity of the system as to these three types of multiple image has also been investigated using a cascaded iterative algorithm. The security and the multiplexing parameters of the system are analyzed as well.     

Developing an algorithm for compression, multiplexing and enhancement of multiple images

Image compression is one of the important fields that has useful applications in data storage and transmission. In this research a new algorithm is developed and tested for multiple-image compression and enhancement. The algorithm, in addition, is applied to multiple noisy images. Also, the effect of compression ratio on the peak signal to noise ratio (PSNR) is explored by applying different compression ratios. The developed algorithm gives good compression and noise immunity. It can be used for storage/transmission of encrypted and compressed information.