Color image watermark decoder by modeling quaternion polar harmonic transform with BKF distribution

It still remains a challenging problem to improve both of the imperceptibility and robustness for the digital image watermarking task. In this study, a color image watermarking scheme is proposed based on quaternion polar harmonic transform (QPHT) with maximum likelihood decoder, which better balances imperceptibility and robustness in a novel fashion. Thanks to the strong robustness of QPHT, the digital watermark is embedded into the QPHT magnitudes using a multiplicative approach. At the receiver, the watermark decoder can be formulated as a problem of weak signal detection, as the QPHT magnitudes are highly non-Gaussian. In view of this, selection of proper models is of great importance to construct a suitable watermark decoder. Further, we validate that the probability density function of Bessel K form suitably models the heavy tail behavior of QPHT magnitudes, and thus the maximum likelihood decoder is developed by modeling QPHT magnitudes with Bessel K form distribution. Experimental results on standard benchmarks demonstrate that the proposed approach provides better imperceptibility and robustness against various kinds of attacks compared to previous state-of-the-art methods.     

Geometrically invariant image watermarking based on fast Radial Harmonic Fourier Moments

In order to reduce the time complexity and improve the reconstruction performance of traditional method for Radial Harmonic Fourier Moments (RHFMs), we introduce a fast and precise method by using FFT and based on the which, this paper proposes a novel image watermarking algorithm which is robust to geometric attacks. We firstly compute the RHFMs of the original image by using the proposed method and select the robust RHFMs which are suitable for watermark embedding. Then the watermark is embedded by modifying the magnitudes of RHFMs based on quantization. In the decoder, the watermark can be extracted from the magnitudes of RHFMs directly without using the original image. Simulation results show the proposed algorithm provides an excellent watermark invisibility and can be resilient to geometric attacks and common image processing attacks effectively.     

Contourlet domain locally optimum image watermark decoder using Cauchy mixtures based vector HMT model

Digital image watermarking has become a necessity in many applications such as data authentication, broadcast monitoring on the Internet and ownership identification. Various watermarking schemes have been proposed to protect the copyright information. There are three indispensable, yet contrasting requirements for a watermarking scheme: imperceptibility, robustness and payload. Therefore, a watermarking scheme should provide a trade-off among these requirements from the information-theoretic perspective. Generally, in order to enhance the imperceptibility, robustness and payload simultaneously, the human visual system (HVS) and the statistical properties of the image signal should be fully taken into account. The statistical model-based transform domain multiplicative watermarking scheme embodies the above ideas, and therefore the detection and extraction of the multiplicative watermarks have received a great deal of attention. The performance of a statistical model-based watermark detector or decoder is highly influenced by the accuracy of the statistical model itself and the applicability of decision rule. In this paper, we firstly propose a new hidden Markov trees (HMT) statistical model in Contourlet domain, namely Cauchy mixtures-based vector HMT (vector CMM–HMT), by describing the marginal distribution with Cauchy mixture model (CMM) and grouping Contourlet coefficients into a vector, which can capture both the subband marginal distributions and the strong dependencies across scales and orientations of the Contourlet coefficients. Then, by modeling the Contourlet coefficients with vector CMM–HMT and employing locally most powerful (LMP) test, we develop a locally optimum image watermark decoder in Contourlet domain. We conduct extensive experiments to evaluate the performance of the proposed blind watermark decoder, in which encouraging results validate the effectiveness of the proposed technique, in comparison with the state-of-the-art approaches recently proposed in the literature.     

Image watermarking using DNST-PHFMs magnitude domain vector AGGM-HMT

Invisibility, robustness and payload are three indispensable and contradictory properties for any image watermarking systems. Therefore, in this paper a novel statistical image watermark decoder based on robust discrete nonseparable Shearlet transform (DNST)-polar harmonic Fourier moments (PHFMs) magnitude and effective vector anisotropic generalized Gaussian mixtures (AGGM)-hidden Markov tree (HMT). We begin with a detailed study on the robustness and statistical characteristics of local DNST- PHFMs magnitudes of natural images. This study reveals the excellent robustness, highly non-Gaussian marginal statistics and strong dependencies of local DNST-PHFMs magnitudes. We also find that conditioned on their generalized neighborhoods, the local DNST-PHFMs magnitudes can be approximately modeled as anisotropic generalized Gaussian variables. Based on these findings, we model local DNST-PHFMs magnitudes using a vector AGGM-HMT that can capture all interscale, interdirection, and interlocation dependencies. Meanwhile, model parameters can be estimated effectively by using localization clues guided expectation–maximization (LCGEM) approach. Finally, we develop a new statistical image watermark decoder using the vector AGGM-HMT and maximum likelihood (ML) decision rule. Extensive experimental results show the superiority of the proposed watermark decoder over several state-of-the-art statistical watermarking methods and some approaches based on convolutional neural networks.     

BGGMM-HMT based locally optimum image watermark detector in high-order NSST difference domain

Imperceptibility, robustness and data payload are three main requirements of any image watermarking systems to guarantee desired functionalities, but there is a tradeoff among them from the information-theoretic perspective. How to achieve this balance is a major challenge. In this paper, we propose a new statistical image watermarking scheme, which is based on the high-order difference coefficients in nonsubsampled Shearlet transform (NSST) domain and the bounded generalized Gaussian mixture model-based hidden Markov tree (BGGMM-HMT). In the watermark embedding process, we use a nonlinear embedding approach to hide the digital watermark into the robust high-order difference coefficients, which can achieve better imperceptibility. In the watermark detection process, high-order difference coefficients are accurately modeled by using BGGMM-HMT, where the distribution characteristics of high-order difference coefficients can be captured through BGGMM, and the scale dependencies of high-order difference coefficients can be captured through HMT. Statistical model parameters are then estimated by combining the approach of minimizing the higher bound on data negative log-likelihood function and upward–downward algorithm. Finally, an image watermark detector based on BGGMM-HMT is developed using the locally optimum (LO) decision rule. For the proposed detector, the receiver operating characteristic (ROC) expression is derived in detail. We evaluate the proposed scheme from different aspects and compare it with the state-of-the-art schemes. After a large number of experimental tests, the encouraging results obtained prove the effectiveness of our watermarking scheme.     

自适应的混合域音频水印新算法

本文结合小波包变换和离散余弦变换，提出了一种基于听觉模型的混合域自适应音频盲水印算法，在不引入听觉失真的前提下，实现了自适应的水印嵌入。算法首先对音频信号进行小波包分解，使得分解后的子带更接近人耳临界频带。其次对每个子带的小波包系数进行离散余弦变换，计算出子带掩蔽阈值。根据子带掩蔽阈值自适应的选取噪声敏感度小的音频段作为水印嵌入段，选取功率值低于掩蔽阈值的频域系数作为水印嵌入位置，同时采用噪声掩蔽比调整水印嵌入强度。二值水印图像通过量化索引调制的方法嵌入到音频信号的中低频系数中，提取水印时不需要原始音频载体。本算法在水印容量、不可感知性和鲁棒性之间达到了很好的平衡，水印容量在576.7bps到689.5bps之间，算法对添加噪声、重新量化、重新采样、低通滤波和MP3压缩均具有很好的鲁棒性。      

基于离散余弦变换的图像半盲水印技术研究

结合Arnold变换置乱和频谱系数相关性检测方法,提出了一种基于离散余弦变换域频谱系数相关性检测的半盲水印方案。通过不同嵌入强度的仿真实验,结果表明在嵌入强度k为2.5时达到最大嵌入量,其含水印图的峰值信噪比为30.489 2 dB,相似度达到0.998 9。通过攻击测试表明提出的水印方案具有较好的稳健性。综合仿真实验和攻击测试结果,表明提出的水印方案较好的保证了水印的不可感知性、稳健性与水印容量之间的平衡。     

Robust digital watermarking algorithm based on continuous hyperchaotic system and discrete wavelet transform

Many digital watermarking methods have been pro-posedin the last fewyears[1 ,3].It is a tradeoff problemsince whenthe robustness of a watermarkincreases ,theperceptual quality of the contents will be degraded.Hence,the main goal of i mproving a watermarki…     

A New Audio Watermarking Scheme Based on Singular Value Decomposition and Quantization

In this paper, we propose a new robust and blind audio watermarking algorithm based on singular value decomposition and quantization index modulation. The watermark insertion and extraction methods are based on quantization of the norm of singular values of the blocks. Audio quality evaluation tests show high imperceptibility of the watermark in the audio signal. Simulation results demonstrate that this algorithm is robust against signal-processing and stirmark attacks. The false negative error probability under the proposed scheme is close to zero. Moreover, the proposed algorithm has higher data payload and better performance than the other related audio watermarking schemes available in the literature.     

Video scene characteristic detection to improve digital watermarking transparency

A new method of video scene content characteristic detection is proposed. This method can be applied in conjunction with digital watermarking schemes in order to improve the transparency. In addition, new methods of video watermarking are also proposed. Three related original aspects are reported. First, the authors' previous robust image watermarking methods, which consider the block texture are extended into video. In the detection process, watermark extraction with or without the original frame is provided. Secondly, a method is proposed to improve imperceptibility by reducing the flickering effect. Finally, a method is introduced to detect video scene characteristics in order to suit the particular embedding scheme. By doing so, the embedding method can be chosen adaptively in accordance with the video scene. The subjective tests illustrate an imperceptibility improvement and experiments with various attacks show the watermarking robustness.     

基于Contourlet变换的稳健性图像水印算法

提出了基于Contourlet变换的数字图像水印算法。与小波变换不同的是,Contourlet变换采用类似于线段(contoursegment)的基得到一种多分辨、局部化、方向性的图像表示。水印信号通过基于内容的乘性方案加载到Contourlet变换系数。在采用零均值广义高斯分布拟合Contourlet变换系数的基础上,提出采用极大似然估计实现水印的盲检测。依据Neyman-Pearson准则,在给定虚警率的情况下对判决准则进行了优化。实验结果表明在保证水印隐蔽性的前提下,水印对常见的信号处理手段以及几何变换具有很好的稳健性。     

Progressive Watermarking Techniques Using Genetic Algorithms

An innovative watermarking scheme based on progressive transmission with genetic algorithms (GAs) is proposed. We implement the watermarking embedding and extraction systems in the transform domain, and apply the JPEG spectral selection mode for scalable transmission of the watermarked image. By employing a GA with a proper fitness function into the watermarking system, both the watermark imperceptibility and watermark robustness requirements are considered and optimized. The number of embedded bits, or the watermark capacity, is much larger than that in other existing algorithms in the literature. Also, the watermark capacity in the proposed algorithm lies within the theoretical limit. In addition, the embedded watermark can be partly extracted at the receiver side even when the watermarked image is being transmitted. Simulation results show both the robustness and the effectiveness of progressive transmission under different attacking schemes and different bandwidth variations. The proposed scheme is directly applicable to scalable coding of multimedia, such as MPEG-4 scalable video coding.     

Design and statistical analysis of a hash-aided image watermarking system

This paper develops a joint hashing/watermarking scheme in which a short hash of the host signal is available to a detector. Potential applications include content tracking on public networks and forensic identification. The host data into which the watermark is embedded are selected from a secret subset of the full-frame discrete cosine transform of an image, and the watermark is inserted through multiplicative embedding. The hash is a binary version of selected original image coefficients. We propose a maximum likelihood watermark detector based on a statistical image model. The availability of a hash as side information to the detector modifies the posterior distribution of the marked coefficients. We derive Chernoff bounds on the receiver operating characteristic performance of the detector. We show that host-signal interference can be rejected if the hash function is suitably designed. The relative difficulty of an eavesdropper's detection problem is also determined; the eavesdropper does not know the secret key used. Monte Carlo simulations are performed using photographic test images. Finally, various attacks on the watermarked image are introduced to study the robustness of the derived detectors. The joint hashing/watermarking scheme outperforms the traditional "hashless" watermarking technique.     

基于EMD的音频水印算法研究

提出了一种基于经验模态分解(Empirical Mode Decomposition,EMD)的音频水印算法,选择EMD分解得到的冗余信号分量作为水印的嵌入位置,并证明了冗余信号分量按照提出的算法嵌入水印以后仍然是冗余信号分量,从而为水印嵌入提取提供了理论基础.通过粒子群优化算法求解出适用于EMD分解的最优音频水印嵌入强度,按此强度嵌入水印,可以同时满足水印的健壮性和不可感知性.仿真结果表明,使用计算出的最优嵌入强度嵌入水印,嵌入水印后的音频信号在受到大部分攻击的情况下可以确保水印的不可见性和健壮性.     

基于压缩感知的鲁棒可分离的密文域水印算法

为了满足密文域水印嵌入的需要,该文基于压缩感知技术,提出一种鲁棒可分离的密文域水印算法。首先,内容拥有者将图像进行不重叠分块,利用边缘检测手段划分重要块和非重要块。重要块用传统加密方式进行加密,非重要块用压缩感知技术进行加密,同时为水印嵌入留出一定空间,然后根据嵌入密钥,实现二值水印的密文嵌入。在接收端获取图像内容和水印的方式是可分离的,同时根据含水印的密文图像块的像素分布特性可重新判断块的属性,避免了传输块属性信息。此外,水印信息重复4次嵌入在密文图像的不同区域,保证了水印的鲁棒性。实验结果显示所提方案在抵抗适度攻击时具有鲁棒性和安全性。     

一种基于曲波变换的数字水印算法

提出了一种基于曲波变换的数字水印算法,该算法将水印信息嵌入到曲波变换的粗尺度系数矩阵中,考虑到水印鲁棒性和不可见性的要求,选择合理的嵌入强度,使得加水印图像的不可见性更好。由于选择了代表图像大多数能量的低频系数嵌入,在抵抗JPEG压缩、噪声攻击、中值滤波等攻击性能方面较理想,因此文中算法具有较强的鲁棒性,能满足水印系统不可见性和鲁棒性的要求。     

一种基于图像特征点的数字水印嵌入方法

如何有效抵抗去同步攻击是数字图像水印研究领域的热点问题之一.本文提出了一种可有效抵抗去同步攻击的图像水印新算法.该算法首先利用Harris-Laplace算子从载体图像中提取尺度空间特征点;再结合特征尺度自适应确定局部特征区域;最后,采纳DFT中频幅值量化策略将水印重复嵌入到多个不相交的局部特征区域中.检测时,利用特征点实现水印的重同步,无须求助于原始图像.仿真结果表明,本文算法不仅具有较好的透明性,而且对常规信号处理和去同步攻击均具有较好的鲁棒性.     

Optimal audio watermarking scheme using genetic optimization

Designing an optimal audio watermarking system is an open difficult issue since its two basic performance measures, i.e., imperceptibility and robustness, are conflicting with each other. So, an optimal audio watermarking scheme needs to optimally balance both imperceptibility and robustness. In order to realize such an optimal watermarking system, by considering the balance as an optimization problem, we propose an optimal audio watermarking scheme using genetic optimization with variable-length mechanism in this paper. The presented genetic optimization procedure can automatically determine optimal embedding parameters for each audio frame of an audio signal. Specially, employed variable-length mechanism can effectively search most suitable positions for watermark embedding, including suitable audio frames and their AC coefficients. By dint of the genetic optimization with variable-length mechanism, proposed audio watermarking scheme can not only guarantee good quality of watermarked audio signal but also effectively improve its robustness. Experimental results show that proposed watermarking scheme has good imperceptibility and high capability against common signal processing and some desynchronization attacks.     

Security analyses of the watermarking scheme based on redundant discrete wavelet transform and singular value decomposition

This study analyzes the recent image watermarking schemes based on redundant discrete wavelet transform (RDWT) and singular value decomposition (SVD), and shows that in fact they are insecure and cannot be used for protecting the rightful ownership. The RDWT-SVD watermarking directly embeds a grayscale watermark image of the same size with the host image into the singular value matrix of the RDWT-transformed host image, then produces the left and right orthogonal matrices as side information which is later used in the watermark extraction stage. The RDWT-SVD approach enjoys the advantage of the RDWT redundancy to achieve a high embedding capacity, and preserves the watermark imperceptibility by exploiting the SVD stability properties. It is claimed that RDWT-SVD watermarking is robust against several common image processing and geometrical attacks, yet a fundamental flaw in the RDWT-SVD scheme is found, which leads to severe the false positive issue. Three vulnerable attacks should be considered in the RDWT-SVD scheme: (1) An attacker can easily claim the owner watermarked image; (2) the owner has the ambiguity because of the wrong side information usage, and (3) the owner can extract the correct watermark from arbitrary image. Thus, it is important to highlight these attacks when implementing the RDWT-SVD watermarking scheme.     

Multiscale fragile watermarking based on the Gaussian mixture model.

In this paper, a new multiscale fragile watermarking scheme based on the Gaussian mixture model (GMM) is presented. First, a GMM is developed to describe the statistical characteristics of images in the wavelet domain and an expectation-maximization algorithm is employed to identify GMM model parameters. With wavelet multiscale subspaces being divided into watermarking blocks, the GMM model parameters of different watermarking blocks are adjusted to form certain relationships, which are employed for the presented new fragile watermarking scheme for authentication. An optimal watermark embedding method is developed to achieve minimum watermarking distortion. A secret embedding key is designed to securely embed the fragile watermarks so that the new method is robust to counterfeiting, even when the malicious attackers are fully aware of the watermark embedding algorithm. It is shown that the presented new method can securely embed a message bit stream, such as personal signatures or copyright logos, into a host image as fragile watermarks. Compared with conventional fragile watermark techniques, this new statistical model based method modifies only a small amount of image data such that the distortion on the host image is imperceptible. Meanwhile, with the embedded message bits spreading over the entire image area through the statistical model, the new method can detect and localize image tampering. Besides, the new multiscale implementation of fragile watermarks based on the presented method can help distinguish some normal image operations such as JPEG compression from malicious image attacks and, thus, can be used for semi-fragile watermarking.