基于双随机相位的彩色图像加密隐藏技术

为了能够完全无失真的提取隐藏图像,在双随机相位加密的基础上,提出了一种对彩色图像进行加密隐藏的方法.通过构造宿主图像矩阵,可以将待隐藏的彩色图像编码信息的实部和虚部同时隐藏于该宿主图像矩阵中,避免了已有方法需要传输多幅图像的不足.模拟实验结果表明,该方法不仅安全系数高,保密效果好,而且能完全无失真的提取隐藏图像.     

一种基于双随机相位编码的高容量信息隐藏算法

针对一种基于双随机相位编码的图像隐藏算法进行了改进,实现了更高容量的信息隐藏。该算法对于待隐藏图像进行双随机相位编码之后,将编码图像嵌入到以一定方式扩展的宿主图像中得到混合图像。在嵌入编码图像时采用了不同于原方法的叠加方式,从而提高了信息隐藏量。此外,与原方法相比,在保持恢复的隐藏图像质量的同时,改善了混合图像的质量,且明显增强了算法安全性。理论分析及实验均证明了方法的有效性。     

基于SVD的灰度水印单色通道嵌入算法

为了更有效地进行多媒体数据的版权保护,提出了一种在真彩色宿主图像中利用奇异值分解实现的灰度水印嵌入的鲁棒算法。该算法首先利用奇异值的特征来对灰度水印图像进行编码预处理,编码后的水印信息存储为二值数字序列,并选择视觉掩蔽性高的宿主图像区域进行隐藏。为了保证水印的不可察觉性,该水印算法先提取宿主图像RGB彩色空间中的蓝色通道分量,然后选择其中具有高活动因子的图像分块作为水印的嵌入区域。用该算法对灰度水印图像进行处理,不仅实现了水印的盲提取,而且在保证隐藏灰度水印大容量生动信息的同时,对宿主图像的视觉效果影响很小。实验结果表明,该水印算法不仅较传统方法有更高的鲁棒性,而且灰度水印图像的提取结果受常见的图像处理攻击操作的影响非常小。     

基于宿主图像差值矩阵的可逆信息隐藏算法

提出一种能无失真地从水印图像中提取出隐藏信息并无失真地恢复出原始图像的可逆图像信息隐藏算法。该算法利用图像相邻像素之间差异较小的特性,通过差值矩阵对原始图像进行预处理,修改差值矩阵并映射到宿主图像中实现信息隐藏。理论分析和仿真实验表明,该算法在保证良好不可见性的情况下,有效提高了信息嵌入容量。     

多核学习纹理特征的无参考图像质量评价

由于多种失真类型灰度-共生矩阵特征的不规则性,单核方法无法取得理想结果,从而提出了一种基于多核学习,针对多种失真类型的无参考图像质量评价方法。首先对灰度图像进行相位一致和结构张量变换,得到相位一致图和结构张量图,然后分别对它们提取灰度-梯度共生矩阵二次统计特征,最后将提取的特征输入到高效的分层多核学习机进行训练学习,预测得到图像的质量评分。多图像库多次随机实验结果表明,新方法结果与主观评价值有较好的一致性,并具有较好的推广性。     

基于预测误差编码的加密域可逆数据隐藏算法

为提高加密图像可逆数据隐藏的嵌入容量与安全性,提出一种改进的加密域可逆数据隐藏算法。以分块加密方式保留图像块内相邻像素间的相关性,利用多元线性回归模型对图像块内特定像素进行预测,同时以位替换方式将预测误差码元和秘密信息同时嵌入目标像素中,通过差分对称编码提升编码效率并扩展嵌入空间,使得接收者在仅拥有加密密钥和嵌入密钥的情况下可无失真地恢复原始图像和提取秘密信息。实验结果表明,该算法在BOWS-2和UCID数据集上的平均嵌入率分别达到1.717和1.310 bit/pixel,在提高嵌入容量和安全性的同时实现了信息提取操作和图像恢复操作的完全分离。     

基于纠错码的健壮性图像信息隐藏算法

针对空域图像信息隐藏(IH)算法健壮性较差的缺陷,研究了基于纠错码的图像信息隐藏算法。利用纠错码能够纠正随机错误的特性提高空域信息隐藏算法抵抗攻击者修改载体的能力。给出了两类不同的算法:基于纠错码的最低有效位(LSB)信息隐藏算法与基于纠错码的灰度位信息隐藏算法。前者将秘密信息进行编码并以LSB的形式进行嵌入,能够在低密度噪声的情况下实现较高的健壮性;后者利用图像像素灰度值的结构特点,以Hamming码的形式对每一个已嵌入秘密信息的像素灰度值进行编码,可以达到独立纠正一个错误的目的。理论分析和实验结果表明,在相同的噪声密度和噪声幅度下,这两类算法恢复的秘密信息百分比均高于基本的LSB算法,是两种具有较高健壮性的信息隐藏算法。     

偶数长有理数对称紧支双正交小波滤波器设计

基于Daubechies紧支集小波构造方法所得到的小波滤波器多为非线性相位和无理数系数。非线性相位滤波器在图像处理过程中容易引起失真,而无理系数滤波器给小波变换的应用尤其是在算法的硬件实现方面带来不便。借助完全重构滤波器思想,进行了具有线性相位的双正交小波滤波器设计,同时通过添加消失矩特性条件,归纳推导出偶数长有理系数双正交对称紧支集小波滤波器的构造方法。以长度为8-4双正交小波设计为例,对设计方程中出现的自由变量的取值范围进行了讨论,得到了8-4有理系数双正交对称小波滤波器。     

一种使用正交分形编码的彩色图像水印算法

传统的正交分形水印算法,很多情况下只是针对灰度宿主图像,且嵌入的水印多为随机序列或二值图像,实用性不强.当这些算法在处理彩色宿主图像时,通常采用的是将R,G,B三个分量单独处理的SFC方法,没能考虑到分量之间的相关性,因此算法的鲁棒性较弱.文提出一种在彩色图像中利用正交分形编码嵌入灰度水印的算法,该算法在对彩色宿主图像进行正交分形编码的基础上,考虑彩色图像R,G,B三个分量的相关性以及拼贴误差特性,通过变换函数以及修改分形编码参数来嵌入灰度水印.实验及应用表明,该算法隐蔽性强,并对剪切、涂抹、加噪以及JPEG压缩等具有较强的鲁棒性.     

傅里叶相位图水印隐藏的实现与应用

采用待隐藏图像的相位图作为数字水印嵌人宿主图像,实现了信息隐藏,与隐藏图像同时具有振幅信息和相位信息的情况比较,需要隐藏的信息量显著降低.相应的水印提取数据仅是图像的相位信息,并将提取出的傅里叶相位图像与一幅新图像的傅里叶振幅图像结合,原始隐藏图像被恢复,验证了图像的相位的主导性,且运用这种特性可有效地实现信息的隐藏与恢复.利用图像所具有的迷惑性产生的信息隐藏更能起到掩护的作用.     

Symmetric keys image encryption and decryption using 3D chaotic maps with DNA encoding technique

In present digital era, multimedia like images, text, documents and videos plays a vital role, therefore due to increase in usage of digital data; there comes high demand of security. Encryption is a technique used to secure and protect the images from unfair means. In cryptography, chaotic maps play an important role in forming strong and effective encryption algorithm. In this paper 3D chaotic logistic map with DNA encoding is used for confusion and diffusion of image pixels. Additionally, three symmetric keys are used to initialize 3D chaos logistic map, which makes the encryption algorithm strong. The symmetric keys used are 32 bit ASCII key, Chebyshev chaotic key and prime key. The algorithm first applies 3D non-linear logistic chaotic map with three symmetric keys in order to generate initial conditions. These conditions are then used in image row and column permutation to create randomness in pixels. The third chaotic sequence generated by 3D map is used to generate key image. Diffusion of these random pixels are done using DNA encoding; further XOR logical operation is applied between DNA encoded input image and key image. Analysis parameters like NPCR, UACI, entropy, histogram, chi-square test and correlation are calculated for proposed algorithm and also compared with different existing encryption methods.

     

A novel joint secret image sharing and robust steganography method using wavelet

In this paper a data hiding method is proposed based on the combination of a secret sharing technique and a novel steganography method using integer wavelet transform. In this method in encoding phase, first a secret image is shared into n shares, using a secret sharing technique. Then, the shares and Fletcher-16 checksum of shares are hidden into n cover images using proposed wavelet based steganography method. In decoding phase, t out of n stego images are required to recover the secret image. In this phase, first t shares and their checksums are extracted from t stego images. Then, by using the Lagrange interpolation the secret image is revealed from the t shares. The proposed method is stable against serious attacks, including RS and supervisory training steganalysis methods, it has the lowest detection rate under global feature extraction classifier examination compared to the state-of-the-art techniques. Experimental results on a set of benchmarks showed that this method outperforms conventional methods in offering a high secure and robust mechanism for joining secret image sharing and steganography.     

一种基于菲涅耳变换的信息隐藏算法研究

为了提高网络传输信息的保密性能,提出了一种基于菲涅耳变换的隐藏算法,该算法将两幅尺寸同为[N×N]的可视隐藏信息进行菲涅尔变换,将变换得到的实部与虚部随机地加载于尺寸为[2N×2N]可视图像相应像素的邻近位置.考虑到可视图像像素的最大灰度值为255,采取特定方式对载体可视图像的灰度值进行了处理。该算法将信息的嵌入方式、光波长和衍射距离等信息作为密钥,安全性高,并且能够获得高质量的重建图像。实验证明该算法具有一定的实用性。     

Hidden image display which required the special eyeglass for the viewer to observe the hidden image

Stenography is to conceal the hidden information within another information such that the hidden information can be extracted by the special technique. A steganographic display that required the special eyeglass for the viewer to observe the hidden image was newly proposed. In this hidden‐image display, the viewers wearing the special eyeglass can observe the hidden image, while the viewer with the naked eye can not discern the hidden image. Working principle and the calculation scheme for the generation of input images was investigated. The estimation of the normalized luminance for the gray levels of each pixel on the display was required for the calculation. The concept was experimentally verified using the commercial 3D display based on the patterned retarder and the polarizing eyeglass.     

Unsupervised statistical segmentation of nonstationary images using triplet Markov fields

Recent developments in statistical theory and associated computational techniques have opened new avenues for image modeling as well as for image segmentation techniques. Thus, a host of models have been proposed and the ones which have probably received considerable attention are the hidden Markov fields (HMF) models. This is due to their simplicity of handling and their potential for providing improved image quality. Although these models provide satisfying results in the stationary case, they can fail in the nonstationary one. In this paper, we tackle the problem of modeling a nonstationary hidden random field and its effect on the unsupervised statistical image segmentation. We propose an original approach, based on the recent triplet Markov field (TMF) model, which enables one to deal with nonstationary class fields. Moreover, the noise can be correlated and possibly non-Gaussian. An original parameter estimation method which uses the Pearson system to find the natures of the noise margins, which can vary with the class, is also proposed and used to perform unsupervised segmentation of such images. Experiments indicate that the new model and related processing algorithm can improve the results obtained with the classical ones.     

一种基于ICA的汉字信息隐秘传输方法

本文描述了一种基于独立成份分析(ICA)的汉字信息隐密传输方法。该方法以彩色图像为寄主图像,对其进行ICA分解,求出其中的独立成分,再将汉字信息以编码形式,隐藏在对彩色图像质量影响最小的独立成分低位端,从而实现汉字信息的隐秘传输。该方法已经在PC机上进行了模拟,实验结果表明,该方法在保证图像质量条件下,有较高的嵌入率和较好的可靠性。     

一种基于PCA的数字音频信息隐秘传输方法

描述了一种基于主成分变换（PCA）的数字音频信息隐密传输方法。该方法以彩色图像为寄主图像，对其进行PCA分解，将经压缩、加密、纠错编码后的数字音频码流，隐藏在对彩色图像质量影响最小的PCA变换数据中，生成藏音图像进而实现音频信息的隐密传输。PC机上进行模拟实验的结果表明，该方法在保证图像质量条件下，有较高的嵌入率、较好的可靠性与隐蔽性。