基于QR码与混沌加密的Contourlet域彩色图像盲水印算法

目的针对现行数字水印算法中抗几何攻击能力弱以及嵌入水印信息容量差的问题,提出一种Contourlet变换下QR码与混沌加密相结合的彩色图像水印算法。方法采用QR码作为水印图像,利用Logistic混沌序列对其进行加密,再将加密的水印图像嵌入到二级Contourlet变换的低通子带中,利用系数间的大小关系,修改系数完成水印嵌入与提取。结果通过实验结果可知,水印的嵌入对载体图像影响较小,PSNR值高达42.764,经过旋转、剪切及常规攻击后,提取出的水印均可正确解码。结论该算法具有良好的安全性、不可见性,对于各类攻击具有较优的鲁棒性。水印信息容量高于普通图像,水印提取方式为盲提取,能够更好地满足各类数字作品版权保护的实际需要。     

一种基于 Contourlet 变换的彩色图像全息水印算法

提出了一种结合了全息水印加密技术和 Contourlet 变换技术的彩色图像水印算法。 算法首先将 RGB 模式的水印载体图像转换至 YCrCb 颜色空间,选取亮度分量作为水印载体通道,对其进行多层 Contourlet 分解,得到细节子带图像;而后对二值水印图像进行傅里叶全息加密,将加密后的图像嵌入至载体图像的 Contourlet变换系数中。 仿真实验结果表明,该水印算法具有良好的不可见性,对于常见的几何变换及多种攻击具有良好的鲁棒性。     

A Robust Zero-Watermarking Based on SIFT-DCT for Medical Images in the Encrypted Domain

Remote medical diagnosis can be realized by using the Internet, but when transmitting medical images of patients through the Internet, personal information of patients may be leaked. Aim at the security of medical information system and the protection of medical images, a novel robust zero-watermarking based on SIFT-DCT (Scale Invariant Feature Transform-Discrete Cosine Transform) for medical images in the encrypted domain is proposed. Firstly, the original medical image is encrypted in transform domain based on Logistic chaotic sequence to enhance the concealment of original medical images. Then, the SIFT-DCT is used to extract the feature sequences of encrypted medical images. Next, zero-watermarking technology is used to ensure that the region of interest of medical images are not changed. Finally, the robust of the algorithm is evaluated by the correlation coefficient between the original watermark and the attacked watermark. A series of attack experiments are carried out on this method, and the results show that the algorithm is not only secure, but also robust to both traditional and geometric attacks, especially in clipping attacks.     

一种抗任意角度旋转的全息水印算法

目的针对目前数字水印在抗旋转攻击方面鲁棒性较差等问题,提出一种基于DWT变换和仿射变换的抗任意角度旋转的数字全息水印算法。方法首先对数字水印进行全息加密,保证水印的安全性;结合DWT变换,将水印信息嵌入载体图像;然后通过仿射变换实现图像的角度校正,进而实现抗任意角度旋转攻击及其他常见攻击。结果水印在受到各种攻击后,仍能被有效提取,尤其是抗任意角度旋转攻击,NC值均大于0.6。结论提出的算法对任意角度旋转攻击有较强的鲁棒性,可以有效地从含水印的图像中提取水印信息,保证了水印的安全性和有效性。     

抗几何攻击的强鲁棒性全息水印研究

目的寻找一种能够抵抗常见几何攻击的安全的水印算法。方法通过分析常见的水印算法,发现傅里叶-梅林变换域水印能够较好地满足抵抗常见几何攻击的需求。对水印图像进行双随机相位全息加密,通过密钥保障水印的安全性,通过把加密的水印嵌入到傅里叶-梅林变换域的方法,设计对比试验,研究含有水印的图像在平移、缩放、旋转、中值滤波、高斯噪声、椒盐噪声、压缩、打印扫描、打印拍摄攻击下提取水印质量的影响。结果水印能够抵抗常见的几何攻击,特别对平移、缩放、旋转组合几何攻击、打印扫描和打印拍摄有很好的效果。结论基于傅里叶-梅林变换的全息水印算法具有很好的鲁棒性,能够抵抗常见的几何攻击;具有很好的安全性,没有密钥不能对水印进行检测和去除。     

基于方向金字塔分解与稳定几何失真校正的鲁棒图像水印算法

目的为了提高水印算法的抗几何攻击能力,并兼顾较高的鲁棒性与不可感知性,设计一种基于方向金字塔分解与稳定几何失真校正的鲁棒图像水印算法。方法首先,引入方向金子塔,对载体图像完成分解,输出对应的低通与高通子带;将低通子带分割为一系列的非重叠块;根据载体的亮度、纹理与边缘掩码,计算水印嵌入强度,最大程度地平衡水印图像的不可感知性与鲁棒性;设计水印嵌入方法,将经过Arnold映射加密后的水印嵌入到非重叠子块中,通过修改载体的方向金子塔分解系数,获取水印图像;将不同的攻击类型作用于水印图像,建立训练样本;再利用方向金子塔分解训练样本,计算高通子带的高斯-厄米矩能量,将其视为特征矢量;再利用特征矢量对模糊支持向量机完成训练,以预测几何失真参数,准确校正受攻击的水印图像;设计水印检测机制,从水印图像中复原水印。结果实验数据表明,与当前图像水印方案相比,所提算法具有更高的抗几何变换能力,以及较好的不可感知性与鲁棒性,其提取的水印失真度最小,对应峰值信噪比保持在40dB以上。结论所提水印算法具有较高的鲁棒性和视觉隐秘性,在版权保护、信息防伪等领域具有一定的参考价值。     

A Robust Watermarking Scheme Based on ROI and IWT for Remote Consultation of COVID-19

In the current dire situation of the corona virus COVID-19, remote consultations were proposed to avoid cross-infection and regional differences in medical resources. However, the safety of digital medical imaging in remote consultations has also attracted more and more attention from the medical industry. To ensure the integrity and security of medical images, this paper proposes a robust watermarking algorithm to authenticate and recover from the distorted medical images based on regions of interest (ROI) and integer wavelet transform (IWT). First, the medical image is divided into two different parts, regions of interest and non-interest regions. Then the integrity of ROI is verified using the hash algorithm, and the recovery data of the ROI region is calculated at the same time. Also, binary images with the basic information of patients are processed by logistic chaotic map encryption, and then the synthetic watermark is embedded in the medical carrier image using IWT transform. The performance of the proposed algorithm is tested by the simulation experiments based on the MATLAB program in CT images of the lungs. Experimental results show that the algorithm can precisely locate the distorted areas of an image and recover the original ROI on the basis of verifying image reliability. The maximum peak signal to noise ratio (PSNR) value of 51.24 has been achieved, which proves that the watermark is invisible and has strong robustness against noise, compression, and filtering attacks.     

基于DWT-SVD 的强鲁棒全息水印算法研究

在理论分析全息水印和变换域水印的基础上,提出了基于DWT-SVD 的强鲁棒全息水印算法,通过MAT-LAB 仿真软件对该水印算法进行了仿真,验证了该水印算法的安全性、鲁棒性和不可见性。双随机相位调制加密全息技术对水印信息进行加密具有较高的安全性;在DWT 和SVD 变换域中嵌入水印能够保证水印的不可见性及鲁棒性;结合全息技术和DWT-SVD 的特性,克服了现有水印算法不抗旋转的缺点。该算法首先对水印信息进行加密,获取其奇异值;然后对载体RGB 图像的B 分量进行小波分解,获取其2 次小波分解后低频系数的奇异值;最后用加权的方法嵌入水印。水印嵌入与提取仿真实验结果为PSNR>20 dB,NC 值接近于1,说明该算法的可行性;鲁棒性仿真实验表明该算法能够抵抗任意旋转攻击及基本图像处理操作的攻击。     

Robust image watermarking scheme against geometric attacks using a computer-generated hologram

Robustness against geometric attacks is one of the most important issues in digital watermarking. A novel geometric robust watermarking scheme that uses computer-generated holograms as the watermark is presented. To maintain imperceptibility and robustness, a quantization embedding algorithm is adopted to embed the mark hologram into the low-frequency subband of the wavelet-transformed host image. In the detection process, the geometric distorted watermarked images are recovered first by the proposed improved geometric correction method, which is based on the scale invariant feature transform, the invariant centroid, and the pulse coupled neural network. Then the mark holograms are extracted from the recovered images. In comparison with the traditional geometric estimation method, the suggested improved geometric correction method can estimate the geometric distortion parameters more accurately and needs less auxiliary information. Compared with other watermark schemes using digital holograms, the proposed method has the distinct advantage of robustness to geometric attacks. The experimental results demonstrate that the proposed method has good robustness to resist geometric attacks and common attacks including rotation, scaling, translation, image flipping, combined attacks, filtering, occlusion, cropping, and JPEG compression.     

Robust Multi-Watermarking Algorithm for Medical Images Based on GoogLeNet and Henon Map

The field of medical images has been rapidly evolving since the advent of the digital medical information era. However, medical data is susceptible to leaks and hacks during transmission. This paper proposed a robust multi-watermarking algorithm for medical images based on GoogLeNet transfer learning to protect the privacy of patient data during transmission and storage, as well as to increase the resistance to geometric attacks and the capacity of embedded watermarks of watermarking algorithms. First, a pre-trained GoogLeNet network is used in this paper, based on which the parameters of several previous layers of the network are fixed and the network is fine-tuned for the constructed medical dataset, so that the pre-trained network can further learn the deep convolutional features in the medical dataset, and then the trained network is used to extract the stable feature vectors of medical images. Then, a two-dimensional Henon chaos encryption technique, which is more sensitive to initial values, is used to encrypt multiple different types of watermarked private information. Finally, the feature vector of the image is logically operated with the encrypted multiple watermark information, and the obtained key is stored in a third party, thus achieving zero watermark embedding and blind extraction. The experimental results confirm the robustness of the algorithm from the perspective of multiple types of watermarks, while also demonstrating the successful embedding of multiple watermarks for medical images, and show that the algorithm is more resistant to geometric attacks than some conventional watermarking algorithms.     

一种抗旋转的全息水印算法

为了找到一种能够抵抗旋转攻击的安全的水印算法,综合分析了常见的水印算法后,发现离散小波变换、离散余弦变换、奇异值分解的变换域水印能够较好地满足抗旋转攻击的需求。对水印图像进行了双随机相位全息加密,通过密钥保障水印的安全性,把加密的水印嵌入到变换域中。设计了试验,研究了含有水印的图像在平移、缩放、旋转、中值滤波、高斯噪声、椒盐噪声和压缩攻击下提取水印质量的影响。实验结果表明,水印能够抵抗常见的几何攻击,特别是旋转攻击,对常见的噪声压缩攻击同样有很好的效果。基于变换域的全息水印算法具有很好的鲁棒性,能够抵抗常见的几何攻击,具有很好的安全性,没有密钥不能对水印进行检测和去除。     

一种强鲁棒性的彩色图像数字水印技术

目的提出了一种彩色图像数字水印技术,解决数字水印在大数据量水印、不可见性和鲁棒性之间的关系。方法该算法对彩色QR码水印和彩色载体图像分别进行RGB三通道分解,彩色水印单通图像进行混沌加密;对彩色载体单通道图像进行Contourlet变换;按对应通道将水印嵌入到载体图像低频经奇异值分解后的对角矩阵。结果该算法在水印嵌入和提取仿真实验结果为PSNR50 d B;鲁棒性仿真实验结果表明,该算法在抵抗任意旋转攻击和基本图像处理操作的攻击下,提取出来的彩色QR码颜色未失真,并且均能够成功解码和自动识别。结论该算法具有较强的鲁棒性和较好的不可见性,能够很好地将彩色水印嵌入彩色图像,可应用到实际的数字版权保护中。     

一种新的彩色图像变换域全息水印算法

提出了一种变换域中改善全息水印抗几何攻击和滤波攻击性能的彩色图像全息水印算法。 取彩色 RGB载体图像的蓝色通道,分块后做一级小波分解转换到变换域,取低频子带,然后进行奇异值分解嵌入数字全息水印。 实验结果表明:该算法水印隐蔽性好,重建的水印与原始水印相似度高;算法鲁棒性强,可以抵抗常见的各种攻击,尤其改善了全息水印的抗几何攻击和滤波攻击性能,满足了数字防伪、版权保护的需要。     

A Robust Image Watermarking Scheme Using Z-Transform,Discrete Wavelet Transform and Bidiagonal Singular Value Decomposition

Watermarking is a widely used solution to the problems of authentication and copyright protection of digital media especially for images, videos, and audio data. Chaos is one of the emerging techniques adopted in image watermarking schemes due to its intrinsic cryptographic properties. This paper proposes a new chaotic hybrid watermarking method combining Discrete Wavelet Transform (DWT), Z-transform (ZT) and Bidiagonal Singular Value Decomposition (BSVD). The original image is decomposed into 3-level DWT, and then, ZT is applied on the HH3 and HL3 sub-bands. The watermark image is encrypted using Arnold Cat Map. BSVD for the watermark and transformed original image were computed, and the watermark was embedded by modifying singular values of the host image with the singular values of the watermark image. Robustness of the proposed scheme was examined using standard test images and assessed against common signal processing and geometric attacks. Experiments indicated that the proposed method is transparent and highly robust.     

基于IWT-SVD和BRISK的鲁棒图像水印算法

目的 针对数字图像水印中传统奇异值分解算法存在的提取水印对角线失真和目前的特征点匹配算法速度慢引起抗组合几何攻击性能弱问题,提出基于IWT-SVD和BRISK的鲁棒图像水印算法。方法 该方案是将Logistics混沌映射置乱的水印嵌入宿主图像IWT变换后进行SVD分解的矩阵中,然后运用BRISK算法完成失真图像的几何校正,最后根据提取的水印图像特性,用邻域平均法进行对角线元素修正。结果 嵌入水印后PSNR高于42 dB,在各种常规信号处理和组合几何攻击下,NC平均值在0.95以上,提取出的水印对角线失真问题得到明显改善。结论 实验结果表明,该方案能提高图像特征点的匹配速度,性能得到增强,水印不可见性较好,进一步提升了图像的鲁棒性。     

基于整数小波变换与矩阵分解的感兴趣区域可逆水印算法研究

目的针对传统感兴趣区域水印算法抵抗几何攻击能力较弱的缺陷,提出一种基于IWT-Schur的感兴趣区域可逆水印算法。方法首先对载体图像做小波变换,筛选出各子带ROI系数,接着采用Arnold变换加密水印图像,加密水印图像做整数小波变换得到一系列分量。最后结合Schur分解,将水印各分量对应加至载体各子带的ROI。结果采用整数小波变换IWT与矩阵Schur分解的嵌入方式,使得含水印图像的视觉质量良好,算法实现容易。含水印图像没有受到干扰时检测到的水印与原水印一致,含水印图像受到攻击时,也表现出良好的性能,检测到的水印品质较好。结论实验证明,此方案水印提取正确,且感兴趣区域无损恢复。     

Optical watermark scheme based on singular value decomposition ghost imaging and particle swarm optimization algorithm

An optical image watermarking algorithm, based on singular value decomposition (SVD) ghost imaging and multiple transforms, is designed. The watermark image is first encrypted by applying an SVD ghost imaging system, then the encrypted watermark is embedded into the cover image with the help of multiple transforms, including lifting wavelet transform (LWT), discrete cosine transform (DCT), discrete fractional angular transform (DFAT) and SVD. Four sub-band images are produced from the host image by LWT and DCT. The improved DFAT, whose scaling factors and parameter are optimized by particle swarm optimization algorithm, is operated in the new matrix. Afterwards, SVD is executed in the two-part image and the encrypted watermark is embedded in the host image by mutual operation of different matrices. Simulation results validate that the proposed watermark scheme is superior in the aspects of security, robustness and imperceptibility.     

一种基于混沌映射的鲁棒性图形水印算法

提出了一种基于混沌映射的DCT域数字图像水印算法。将含有特定信息的二值序列作为原始水印,利用混沌密码对其进行加密,并在嵌入时再利用混沌映射将水印信息嵌入原始图像的DCT域,使得水印方案具有双重安全性。由于在水印检测时不需要原始图像的参与,该算法实现了水印的盲检测。实验结果表明,用该算法嵌入的水印信息具有不可见性,其对常见的图像处理如JPEG压缩、噪声、滤波以及剪切等具有良好的鲁棒性。     

基于Hough变换旋转校正的QR码全息水印算法

目的为了解决QR码图像不易隐藏水印的难题,提出一种针对QR码载体图像的强鲁棒性频率域数字水印算法。方法利用经双随机相位调制的傅里叶全息技术对水印进行加密,同时对QR码载体图像进行包含高斯模糊以及去除视觉敏感区域的预处理,将全息加密水印的奇异值矩阵加权嵌入到经过二级小波分解的QR码的中频系数后进行还原。Hough变换通过坐标系转换检测QR码图像同方向边缘的直线,后进行旋转校正,以提取水印。结果在合适的嵌入强度下,水印保持了良好的不可见性(PSNR=32.3)。经过二值化攻击、信号处理(滤波、噪声、压缩)、几何变换(平移、旋转、缩放)以及打印扫描处理等一系列攻击,提取出的水印依旧清晰可见。结论提出的算法针对各类攻击有较强的鲁棒性,可抵御任意角度旋转攻击,同时兼顾水印的不可见性,针对QR码的防伪技术具有一定的应用价值。     

Robust Watermarking Algorithm for Medical Images Based on Non-Subsampled Shearlet Transform and Schur Decomposition

With the development of digitalization in healthcare, more and more information is delivered and stored in digital form, facilitating people’s lives significantly. In the meanwhile, privacy leakage and security issues come along with it. Zero watermarking can solve this problem well. To protect the security of medical information and improve the algorithm’s robustness, this paper proposes a robust watermarking algorithm for medical images based on Non-Subsampled Shearlet Transform (NSST) and Schur decomposition. Firstly, the low-frequency subband image of the original medical image is obtained by NSST and chunked. Secondly, the Schur decomposition of low-frequency blocks to get stable values, extracting the maximum absolute value of the diagonal elements of the upper triangle matrix after the Schur decomposition of each low-frequency block and constructing the transition matrix from it. Then, the mean of the matrix is compared to each element’s value, creating a feature matrix by combining perceptual hashing, and selecting 32 bits as the feature sequence. Finally, the feature vector is exclusive OR (XOR) operated with the encrypted watermark information to get the zero watermark and complete registration with a third-party copyright certification center. Experimental data show that the Normalized Correlation (NC) values of watermarks extracted in random carrier medical images are above 0.5, with higher robustness than traditional algorithms, especially against geometric attacks and achieve watermark information invisibility without altering the carrier medical image.