RDWT domain statistical watermark detector using FRHFMs magnitudes and bivariate Cauchy-Rayleigh distribution

Imperceptibility, robustness and data payload, which are complimentary to each other, are widely considered as the three main properties vital for any image watermarking systems. It is a challenging work to design a statistical model-based multiplicative watermarking scheme for achieving the tradeoff among three main properties. In this paper, we propose a novel statistical image watermarking scheme by modeling local redundant discrete wavelet transform (RDWT) and fast Radial harmonic Fourier moments (FRHFMs) magnitudes with bivariate Cauchy-Rayleigh distribution. Our image watermarking scheme consists of two parts, namely, embedding and detection. In the embedding process, RDWT is firstly performed on the host image and RDWT highpass subbands are divided into non-overlapping blocks. Then FRHFMs are computed on RDWT coefficient blocks. And finally, the watermark signal is inserted into robust RDWT-FRHFMs magnitudes through a non-linear multiplicative approach. In the detection process, robust local RDWT-FRHFMs magnitudes are firstly modeled by employing bivariate Cauchy-Rayleigh distribution, which can capture accurately both marginal distributions and strong dependencies of local RDWT-FRHFMs magnitudes. Statistical model parameters are then estimated effectively by the method of logarithmic cumulants (MoLC) approach. And finally, an image watermark detector for multiplicative watermarking is developed using bivariate Cauchy-Rayleigh model and locally most powerful (LMP) test. Also, we utilize the bivariate Cauchy-Rayleigh model to derive the closed-form expressions for the watermark detector. After performance testing and comparison with the experimental results of existing methods, the proposed statistical image watermarking method has achieved relatively ideal results in terms of robustness, imperceptibility and data payload.

     

新式灰度图像盲检测数字水印算法

将冗余离散小波(RDWT)与矩阵Schur分解结合,提出了一种新式灰度图像盲检测数字水印算法。该算法将载体图像进行二级RDWT变换提取其逼近子图低频部分,并将分块后的每个块低频系数进行Schur分解,通过修改Schur分解后的上三角矩阵对角线上的最大能量元素完成对经Fibonacci变换加密后的水印图像的嵌入,水印的提取过程实现了盲提取。实验结果表明,该水印算法水印嵌入的时间仅为0.97s,平均提取水印时间为0.211s,与类似盲水印算法相比,不可见性的PSNR值提高了14.12%,抵抗高斯噪声攻击、椒盐噪声攻击和剪切几何攻击的能力也分别提高了21.32%、17.31%和27.83%。     

An adaptive color image watermarking using RDWT-SVD and artificial bee colony based quality metric strength factor optimization

Image watermarking has emerged as a useful method for solving security issues like authenticity, copyright protection and rightful ownership of digital data. Existing watermarking schemes use either a binary or grayscale image as a watermark. This paper proposes a new robust and adaptive watermarking scheme in which both the host and watermark are the color images of the same size and dimension. The security of the proposed watermarking scheme is enhanced by scrambling both color host and watermark images using Arnold chaotic map. The host image is decomposed by redundant discrete wavelet transform (RDWT) into four sub-bands of the same dimension, and then approximate sub-band undergoes singular value decomposition (SVD) to obtain the principal component (PC). The scrambled watermark is then directly inserted into a principal component of scrambled host image, using an artificial bee colony optimized adaptive multi-scaling factor, obtained by considering both the host and watermark image perceptual quality to overcome the tradeoff between imperceptibility and robustness of the watermarked image. The hybridization of RDWT-SVD provides an advantage of no shift-invariant to achieve higher embedding capacity in the host image and preserving the imperceptibility and robustness by exploiting SVD properties. To measure the imperceptibility and robustness of the proposed scheme, both qualitative and quantitative evaluation parameters like peak signal to noise ratio (PSNR), structural similarity index metric (SSIM) and normalized cross-correlation (NC) are used. Experiments are performed against several image processing attacks and the results are analyzed and compared with other related existing watermarking schemes which clearly depict the usefulness of the proposed scheme. At the same time, the proposed scheme overcomes the major security problem of false positive error (FPE) that mostly occurs in existing SVD based watermarking schemes.     

基于离散小波—奇异值分解的多水印嵌入算法

为提高传统数字图像水印算法的安全性, 解决数字水印对信号处理和几何失真比较敏感的问题, 提出一种新的以离散小波多级分解与奇异值分解相结合的数字图像水印算法. 不同于常见的基于小波变换的数字水印技术, 该方案在原始图像离散小波变换的低频近似区域和高频对角区域中嵌入水印, 在图像的保真度和鲁棒性之间取得较好的折衷. 水印检测时, 将从低频近似区域和高频对角区域中提取出的水印进行比较, 选择效果较好的水印作为最终检测水印. 实验结果表明, 提出的多水印算法对于各种攻击具有较强的鲁棒性.     

Chaotic based secure watermarking approach for medical images

In this paper, a chaotic based secure medical image watermarking approach is proposed. The method is using non sub-sampled contourlet transform (NSCT), redundant discrete wavelet transform (RDWT) and singular value decomposition (SVD) to provide significant improvement in imperceptibility and robustness. Further, security of the approach is ensured by applying 2-D logistic map based chaotic encryption on watermarked medical image. In our approach, the cover image is initially divided into sub-images and NSCT is applied on the sub-image having maximum entropy. Subsequently, RDWT is applied to NSCT image and the singular vector of the RDWT coefficient is calculated. Similar procedure is followed for both watermark images. The singular value of both watermarks is embedded into the singular matrix of the cover. Experimental evaluation shows when the approach is subjected to attacks, using combination of NSCT, RDWT, SVD and chaotic encryption it makes the approach robust, imperceptible, secure and suitable for medical applications.

     

结合混沌的小波变换数字水印技术

本文结合了混沌系统与小波变换实现了数字图像水印的嵌入.利用混沌系统产生的混沌序列对灰度水印图像进行调制,置乱;对待处理图像进行多级小波分解,将调制置乱后的水印按位拆分为八个二值平面,分别嵌入各层的小波系数中,从而实现水印鲁棒性和不可见性的较好结合.     

一种新的大容量数字音频水印嵌入算法

提出了一种新的大容量数字音频水印嵌入算法．该算法具有以下特点：（1）以整型小波变换为基础，不仅降低了舍入误差，而且提高了音频水印的嵌入与检测速度；（2）采纳分段变换及整体修改策略，增强了数字水印嵌入的稳定性；（3）以灰度图像作为数字水印，不仅数据容量大，而且更具层次感和多样性；（4）以保证不可感知性和鲁棒性的良好平衡为前提，实现了数字水印的盲检测．仿真实验表明：所提出的算法不仅具有较好的不可感知性，而且对诸如重新采样、重新量化、低通滤波、MP3压缩、叠加噪声等攻击均具有较好的鲁棒性．     

水印能量估计的一般性框架

数字图像水印技术为网络环境下多媒体数据的传输提供了一个有效的版权保护方案 ,当前大多数的水印算法均利用实验来确定嵌入的水印的最佳能量。该文提出了一个一般性的水印算法框架,可以从理论上计算需嵌入水印的最佳容量或能量,对基于酉变换域方法的数字水印算法而言,该框架可以作为一个有用的指导方法。     

基于遗传算法的多小波数字图像水印算法

提出了一种基于遗传算法的多小波数字图像水印算法,在离散多小波变换(DMT)域中嵌入水印信息,利用遗传算法进行参数优化,提高水印图像的质量和水印的鲁棒性.实验结果表明,在利用遗传算法在GHM多小波变换域中嵌入水印比离散小波变换(DWT)域中嵌入水印更具有鲁棒性.     

Robust logo watermarking using biometrics inspired key generation

In this paper, a novel logo watermarking technique with key concept is proposed using fractional wavelet packet transform (FrWPT), non-linear chaotic map and singular value decomposition (SVD). The core idea is to use biometrically generated keys in the embedding process of gray-scale watermark. Therefore, this paper first proposes a method for generating keys from biometrics efficiently. Then the host image is first randomized with the help of non-linear chaotic map followed by the embedding in the FrWPT domain by modifying the singular values of the randomized image. Further, in order to enhance the security, an authentication key is formed to authenticate the watermarked image. Finally, a reliable extraction process is proposed to extracted watermark from the possibly attacked authenticate watermarked image. The security, attack and comparative analysis confirm high security, efficiency and robustness of the proposed watermarking technique. Further, an efficient solution is also proposed to deal with the ambiguous situations created by SVD in watermarking.     

基于Arnold置乱和小波包分解的自适应水印算法

针对小波变换的不足,根据原始图像各子块对水印信息的适应程度不同,提出一种基于Arnold置乱和小波包分解的自适应水印算法。首先,该算法采用Arnold变换对水印图像进行预处理,然后对原始图像进行小波包分解,小波包分解能够提供一种更为精细的分解方法,将频带进行了多层次的划分,最后将水印图像嵌入到小波包分解后的子带中,水印的嵌入强度和嵌入位置均根据原始图像的内容自适应地决定,这样很好地解决了水印鲁棒性和不可见性之间的矛盾。仿真实验结果表明,算法对常见的图像攻击具有较强的鲁棒性和稳健性。     

一种基于小波包分解的自适应数字水印算法

提出一种基于人类视觉特性和小波包分解的数字水印算法.该算法充分利用小波包分解的特点,将水印信息有选择地嵌入到原始图像中,水印的嵌入强度和嵌入位置均根据原始图像的内容自适应地决定.理论分析和实验结果表明:该算法很好地解决了水印鲁棒性和不可见性之间的矛盾,对一般的图像处理和攻击,如JPEG压缩、滤波、加噪声、裁剪等有很好的鲁棒性.     

小波变换用于基于图像内容的自适应数字水印算法

为了提高在频率域嵌入水印抵抗攻击的能力,该文提出一种基于DWT的CBWM自适应数字水印嵌入算法,该算法依据离散小波变换域的水印嵌入策略:水印应当首先嵌入小波图像的低频系数中,若有剩余,再按小波图像频带重要性的排序,嵌入高频带中,并且水印嵌入到图像的低频系数和高频系数中时,需采用不同的嵌入强度;将水印嵌入到图像三级小波分解变换域的低频空间(LL3)的特征向量中,并且水印与特征向量两者正交。并且,其中水印的嵌入过程是自适应的,即先将小波系数组织成小波块,再依据纹理强弱对小波块分类,然后根据分类结果,将不同强度的水印分量嵌入到特征向量的不同分量中。此外,该算法对静止图像的水印检测是通过Neymann-Pearson决策准则来实现的。实验结果证明,该算法对滤波、噪声、几何变换、图像压缩、以及x-y方向修剪、StirMark攻击等都具有很好的抵抗能力;对裁剪和图像旋转也具有较好的鲁棒性。     

基于线性空间隐藏模型的可逆图像水印算法

提出一种基于线性空间隐藏模型的可逆图像水印算法.通 过对原始图像载体互不重叠的划分形成图像块序列,对其进行整数小波变换,获取待嵌水印子带.根据0/1水印序列和线性空间隐藏模型,将水印不可感知地嵌入到图像的小波域中,提高水印鲁棒性和不可见性. 只需判断奇偶性提取水印,并且通过简单逆向平移恢复原始.线性空间隐藏模型的提出实现了水印间相互独立,从而 使该算法能扩展到多著作权的无损水印领域.投票原则的使用又进一步提高水印的 鲁棒性和降低了误检率.在无外界干扰的条件下,拥有密 钥和其他秘密参数的用户能够无损恢复原始图像.仿真实验表明,与相关工作比较该算 法能应对一定程度的有损压缩和高斯噪声攻击,表现出 较高的鲁棒性、安全性和不可见性.     

抗幅度缩放的小波域自适应数字音频水印算法

数字音频水印的鲁棒性是数字水印领域的研究热点之一。为进一步提高音频水印算法针对幅度缩放等攻击的鲁棒性,借用数字图像归一化的思想,提出了一种基于归一化的抗幅度缩放攻击的数字音频水印算法。该算法首先对音频数据进行自适应分段,然后在空域部分均值化音频数据,最后在三级小波变换的低频系数上以抖动调制的方式实现水印信息的嵌入。实验结果表明所提出的算法对缩放攻击具有很好的鲁棒性,并能够抵抗加噪、低通滤波、重采样、重量化等常见攻击。     

DWT域图像水印的精确嵌入与盲检测的实现

文章提出了一种用于版权认证的基于小波变换的盲图像水印算法,该算法首先从低频子带中选择N个大系数作为嵌入区间,用它们的的低5位表示水印信息;在嵌入过程中,该算法根据小波变换所具有的良好的空域局部化特性,采用了分块舍入技术,实现了水印信息的精确嵌入;在检测过程中,文章提出了一种新颖的差分检测方法,替代了传统的位置检测方法,既简化了检测过程,又增强了系统的鲁棒性。实验结果证明,该算法具有嵌入信息量大,水印透明性好,对各种常见的图像处理操作、有损压缩、裁剪和几何变换抵抗性强等特点。     

基于Fibonacci置乱的小波域数字图像盲水印算法

针对数字图像的版权保护问题,提出一种基于Fibonacci置乱的小波域数字图像盲水印方案。将原图像中的感兴趣区域(ROI)作为水印来源,以此提高水印的隐蔽性。在水印嵌入过程中,将原图像进行分块,对每个块进行Fibonacci置乱和离散小波变换(DWT),选择出低频子带,用于水印嵌入。同时,对水印也执行DWT,选择出低频子带,通过Fibonacci置乱得到置乱矩阵,将水印的置乱矩阵嵌入到主图像的块中。在水印提取过程中,根据嵌入过程中设定的秘钥,通过逆Fibonacci置乱和逆DWT过程提取水印。在多种图像攻击下的仿真结果表明,该水印方案具有较高的安全性、鲁棒性和隐蔽性。     

一种基于混沌和独立成分分析的自适应多重数字水印算法

采用混沌和独立成分分析技术,提出了一种在小波域自适应嵌入多重数字水印的算法。首先根据一个混沌标签序列从原图像中抽取一子图像,并对其进行小波分解,然后将多个互相独立的混沌水印信号依次嵌入到子图像的中频小波系数中,并自适应确定嵌入强度。根据Newman-Pearson准则检测水印是否存在,若存在,采用独立成分分析的方法提取出水印并进一步判断是否为原始水印。水印的检测与提取过程都不需要原始图像。仿真结果表明该算法对各种常见的攻击有着良好的鲁棒性,有效地解决了数字产品的多著作权问题。     

一种基于多尺度空间的图像水印算法

当前数字水印对常见的图像处理攻击如高斯噪声、中值滤波、有损压缩等具有较强的抵抗能力,但其抵抗剪切、缩放等几何攻击的能力较差。因此,为提高数字水印的鲁棒性,结合尺度不变特征变换算子和视觉感知模型,提出一种基于不变特征的水印嵌入方法。基于广义高斯分布模型对小波系数进行刻画,并根据二值假设检验理论确定水印的检测阈值,由此进一步给出水印虚警和漏警之间的工作特性曲线关系。实验仿真结果表明提出的水印方法在抗压缩、叠加噪声、缩放、剪切、旋转等攻击时具有较好的鲁棒性能。     

基于DWT和SVD联合的数字水印算法

离散小波变换(DWT)和奇异值分解都可以作为数字水印算法有效的工具.提出了一种基于离散小波变换和奇异值分解联合的数字水印算法,先将整个图像分成4个区域,然后再对每个区域运用奇异值分解方法,通过修改奇异值来嵌入水印信息.实验结果表明,该算法具有很好的稳健性,在经过了一般的信号处理操作和JPEG压缩后,嵌入的水印能被可靠的提取和检测.