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.     

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.     

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.     

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.     

基于BKF矢量HMT的非下采样剪切波域数字水印检测算法

以非下采样剪切波变换(NSST)及隐马尔可夫树(HMT)理论为基础,提出了一种基于BKF(Bessel K Form)矢量HMT的非下采样剪切波域图像水印算法.水印嵌入时,首先对原始载体图像进行NSST;然后构造自适应高阶水印嵌入强度函数;最后选择重要的NSST高频系数乘性嵌入水印.水印检测时,首先根据NSST系数的非...     

Localized image watermarking in spatial domain resistant to geometric attacks

Watermark robustness to geometric attacks is still a challenging research field. In this paper, a novel robust image watermarking scheme is proposed for resisting such attacks. Watermark synchronization is first achieved by local invariant regions which can be generated using scale normalization and image feature points. The watermark is embedded into all the local regions repeatedly in spatial domain. During embedding, each circular region is first divided into homocentric cirque regions. Then the watermark bits are embedded by quantizing each cirque region into an “odd” or “even” region using odd–even quantization. In the decoder, an odd–even detector (OED) is designed to extract the watermark from the distorted image directly. Localized embedding achieves good invisibility and repeated insertion enhances watermark robustness. Simulation results show that the proposed scheme is robust to both geometric attacks and traditional signal processing attacks.     

基于图像内容的脊波变换域数字水印模型和算法研究

在研究人类视觉(HVS)特性的基础上提出了一种在脊波变换域基于图像内容的数字水印模型。在此模型中,嵌入数字水印的强度归结于数字图像脊波系数的视觉掩盖效应,文中建立了脊波变换域人眼临界可见误差模型。图像的水印检测被归结为Neymann-PeaLrson准则下的统计模型,该模型被用来估算水印检测的最优阈值。作为算例,将临界可见误差模型结合扩展谱技术,提出了一种新颖的图像自适应水印算法,并给出了相应的实验结果。实验表明算法性能大幅度提高。     

RST Invariant Image Watermarking Algorithm With Mathematical Modeling and Analysis of the Watermarking Processes

In this paper, a new rotation and scaling invariant image watermarking scheme is proposed based on rotation invariant feature and image normalization. A mathematical model is established to approximate the image based on the mixture generalized Gaussian distribution, which can facilitate the analysis of the watermarking processes. Using maximum a posteriori probability based image segmentation, the cover image is segmented into several homogeneous areas. Each region can be represented by a generalized Gaussian distribution, which is critical for the analysis of the watermarking processes mathematically. The rotation invariant features are extracted from the segmented areas and are selected as reference points. Subregions centered at the feature points are used for watermark embedding and extraction. Image normalization is applied to the subregions to achieve scaling invariance. Meanwhile, the watermark embedding and extraction schemes are analyzed mathematically based on the established mathematical model. The watermark embedding strength is adjusted adaptively using the noise visibility function and the probability of error is analyzed mathematically. The mathematical relationship between fidelity and robustness is established. The experimental results show the effectiveness and accuracy of the proposed scheme.     

基于Tchebichef不变矩的多比特抗几何攻击图像盲水印算法

现有的大多数水印算法对旋转、平移和尺度变换等几何攻击的鲁棒性比较差,微小的几何攻击都有能导致水印检测器失效,因此水印算法对几何攻击具有鲁棒性非常重要。本文提出了一种基于Tchebichef不变矩实现的多比特几何攻击不变性图像盲水印算法。文中具体介绍了Tchebichef不变矩的构造方法,水印是事先产生的与原始图像无关的信号,嵌入过程中将水印嵌入到图像的Tchebichef不变矩中实现几何攻击不变性。水印检测过程中采用独立分量分析技术实现真正意义上的多比特水印盲检测。文中具体分析了所提出的水印算法的计算复杂度,实验过程中采用通用水印测试软件Stirmark对所提出的水印算法进行鲁棒性测试,实验数据说明这种水印算法对Stirmark具有很好的鲁棒性。     

基于Krawtchouk不变矩的仿射攻击不变性局部水印算法

本文提出了一种基于原始图像Krawtchouk不变矩实现的仿射攻击不变性局部水印算法.具体介绍了Krawtchouk不变矩的构造方法,水印是事先产生的且与原始图像无关,通过将水印嵌入到图像的Krawtchouk不变矩中实现仿射攻击不变性.这种基于Krawtchouk矩的水印算法是局部水印技术,即水印的嵌入只是影响到部分原始图像,因此该算法对剪切攻击具有很好的鲁棒性.检测过程中采用独立分量分析技术实现真正意义上的盲检测.文中具体分析了所提出算法的计算复杂度,实验数据说明这种水印算法对通用水印测试软件Stirmark具有很好的鲁棒性.     

Watermarking scheme based on support vector machine for colour images

A novel watermarking scheme based on the support vector machine is proposed. The watermark is embedded in the blue channel of a colour image. By applying the embedded extra reference watermark, the support vector machine is trained, and then the watermark can be extracted by the trained support vector machine. Owing to the good generalisation ability of the support vector machine, even when the watermarked image is heavily distorted the watermark can be successfully extracted. Experimental results show good robustness of the proposed scheme.     

基于Harris特征点和伪Zernike矩的鲁棒水印算法

抵抗几何攻击的鲁棒性是目前数字水印技术中的热点亦是难点。文中以Harris检测算子和伪Zernike矩为理论基础,提出一种有效抵抗几何攻击的鲁棒水印算法。通过提取归一化图像的Harris特征点,选取部分稳定特征点确定圆形区域并计算伪Zernike矩,并量化调制伪Zernike矩的幅值来嵌入水印信息。实验结果表明,本算法对于抗几何攻击具有较好的鲁棒性,同时也能抵抗常规的信号处理攻击。     

基于自适应频带选择的数字水印技术

如何选择水印的隐藏区域是水印算法中的关键问题。该文提出了一种自适应DCT域水印算法,利用了人眼视觉系统(HVS)和图像局部特性自适应地选择水印隐藏区域,有效地实现了水印的稳定性和不可见性的折衷。与其它水印算法比较,该文提出的自适应算法适合于具有不同总体特性和局部特性的图像。实验结果表明该算法具有很好的感知质量,水印稳健性好,可以抵制各种图像处理操作诸如加性白噪声(AWGN),JPEG压缩以及裁剪,中值滤波,缩放等。     

一种基于特征的自适应水印算法

基于图像多尺度空间理论和扩频机制以及视觉感知模型的特性,给出一种基于特征的数字图像水印算法。算法采用尺度不变特征变换算子提取图像的局部不变特征区域,根据信噪比特点自适应选取水印嵌入强度因子,将一幅二值水印图像嵌入到原始图像中,实现了数字水印的不可感知性和鲁棒性。仿真结果表明,该算法对添加噪声、压缩、旋转等常见的图像处理攻击具有较强的鲁棒性。     

A bilateral attention based generative adversarial network for DIBR 3D image watermarking

This paper presents a bilateral attention based generative adversarial network (BAGAN) for depth-image-based rendering (DIBR) 3D image watermarking to protect the image copyright. Convolutional block operations are employed to extract main image features for robust watermarking, but embedding watermark into some features will degrade image quality much. To relieve this kind of image distortion, the bilateral attention module (BAM) is utilized by mining correlations of the center view and the depth map to compute attention of the 3D image for guiding watermark to distribute over different image regions. Since a modality gap exists between the center view and the depth map, a cross-modal feature fusion module (CMFFM) is designed for BAM to bridge the cross-view gap. Because the depth map has lots of flat background information including many redundant features, to prune them, the depth redundancy elimination module (DREM) is used for cross-view feature fusion. In the decoder, two extractors with the same structure are built to recover watermark from the center view and the synthesized view, respectively. In addition, the discriminator is supposed to build a competitive relationship with the encoder to increase the image quality. The noise sub-network is used to train different image attacks for robustness. Extensive experimental results have demonstrated that the proposed BAGAN can obtain higher watermarking invisibility and robustness compared with existing DIBR 3D watermarking methods. Ablation experiments have also proven the effectiveness of DREM, CMFFM and BAM on BAGAN.     

A Hybrid Approach of DWT and DCT for Rational Dither Modulation Watermarking

In this paper, on the basis of the theories and methods of Watson’s perceptual model and rational dither modulation (RDM), a hybrid quantization-based watermarking in the discrete wavelet transform (DWT) and discrete cosine transform (DCT) domains is studied. In the design of the quantization-based watermarking, quantization step-size plays an important role in many watermarking algorithms. RDM at both the embedder and decoder adopts a gain-invariant adaptive quantization step-size. Therefore, we investigated combining the modified Watson’s perceptual model with RDM. Its improved robustness is due to the embedding in the high entropy region of low-frequency sub-band image and adaptive control of its quantization step-size. The Euclidean distance decoder is used to extract the watermark data. The performance of the proposed scheme is analytically calculated and verified by simulation. Experimental results confirm the imperceptibility of the proposed watermarking and its higher robustness against attacks compared to alternative watermarking methods in the literature.     

基于QDCT和HVS的双彩色图像水印算法

针对水印中信息容量、不可见性和鲁棒性相互制约的问题,文中提出了一种基于QDCT和HVS的双彩色图像水印算法。该算法首先将彩色载体图像和彩色水印图像进行QDCT;然后根据HVS的特性决定水印信息的嵌入位置与嵌入强度,并结合广义Arnold变换和冗余嵌入策略, 将水印QDCT系数嵌入到载体图像QDCT系数的实部和虚部。实验结果表明,通过该算法嵌入水印后的彩色图像在PSNR为35 dB时,在常见攻击下提取出的水印大部分NC值高于0.95,水印信息具有更好的不可见性与鲁棒性。     

一种基于WLD特征的盲检测数字水印算法

提出了一种基于WLD特征的数字图像盲水印算法。在图像WLD特征的基础上通过编码、加密操作生成鲁棒安全的全局水印信息,采用扇形分块方案在图像子块DCT频域中实现水印的嵌入操作。利用WLD全局统计的特性,提取和认证水印的过程无需任何载体图像信息的辅助。实验结果表明,文中盲水印算法的不可感知性较好,同时对加性噪声、伽马校正和剪切操作等具有较好的鲁棒性,算法为认证图像信息的真实性提供了便利。     

基于支持向量回归的Contourlet域盲水印算法

为进一步提高基于支持向量机(SVM,support vector machine)水印算法的性能,提出了基于支持向量回归(SVR,support vector regression)的Contourlet域盲水印算法。首先对宿主图像进行Contourlet分解,然后利用SVM建立图像尺度内的局部相关性模型,根据模型的预测结果自适应地嵌入水印。实验结果表明,所提出的算法不仅具有较好的不可感知性,而且对叠加噪声、JPEG压缩、锐化、平滑滤波和对比度增强等常规图像信号处理以及旋转、剪切等几何攻击均具有较好的鲁棒性,其性能明显优于基于SVM的空间域和小波域的水印算法。