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.     

Embedding in medical images with contrast enhancement and tamper detection capability

This paper presents an efficient data hiding technique capable of providing improved visual quality of watermarked images, besides having the ability to detect the tamper, if any. It is a spatial domain approach in which major emphasis is on improving the visual quality rather than increasing the PSNR or the embedding capacity. The medical images have been divided into Region of Interest (ROI) and Non-Region of Interest (NROI). Bringing out details that lie within the low dynamic range is very important in medical images for effective diagnosis. ROI being diagnostically critical region is enhanced using contrast stretching and subsequently, data is reversibly embedded into the peak bins of ROI. Only those peak bins are employed for reversible data embedding that have an adjacent empty bin to overcome the problem of overflow and underflow. In NROI, the uniform intensity and redundant information region, Least Significant Bit (LSB) embedding is employed for increasing the payload. For tamper detection, a fragile watermark has been embedded in the ROI. To evaluate the scheme various parameters like peak signal to noise ratio (PSNR), No-Reference Quality Metric for contrast-distorted images (NR-CDIQA) and Structural Similarity Index Matrix (SSIM) have been calculated. The experimental results show a remarkable increase in visual quality compared to state-of-art.

     

An efficient and robust watermarking approach based on single value decompression,multi-level DWT,and wavelet fusion with scrambled medical images

This paper offers a medical image watermarking approach based on Wavelet Fusion (WF), Singular Value Decomposition (SVD), and Multi-Level Discrete Wavelet Transform (M-DWT) with scrambling techniques for securing the watermarks images. The proposed approach can be used for providing multi-level security in various applications such as military, copyright protection, and telemedicine systems. The key idea of the projected approach is to first combine two digital watermark images into a single fused watermark to increase the embedded information payload. Then, the fused watermark is scrambled using Arnold and Chaotic algorithms. Finally, the scrambled fused watermark is embedded in the cover image using the SVD and three-level DWT algorithms. The selection of the Arnold and chaotic for watermark encryption is attributed to confirm robustness which resists several types of multimedia attacks and upturn the security level. This paper also presents a comparative study of the proposed approach for different digital images to determine its robustness and stability. Several simulation results reveal that the proposed system improves the capacity and security of embedded medical watermarks without affecting the cover image quality. In conclusion, the proposed approach achieved not only precise acceptable perceptual quality with admired Peak Signal-to-Noise Ratio (PSNR) values but similarly high Correlation Coefficient (Cr) and SSIM values in the existence of severe attacks.

     

结合BEMD与Hilbert曲线的重复嵌入图像水印算法

为解决数字图像水印算法中水印图像与宿主图像在嵌入时尺寸匹配上的局限问题,并提高图像水印算法在抗大尺度剪切、高斯噪声和椒盐噪声等攻击的鲁棒性,提出一种结合二维经验模态分解算法(BEMD)与Hilbert曲线的重复嵌入图像水印算法.首先,利用Arnold变换对水印图像进行置乱处理,以增加水印图像的安全性;其次,利用Hilbert曲线将置乱后的二维水印图像进行数据降维,得到一维水印信号.数据降维不仅有效地解决了嵌入时水印图像与宿主图像在尺寸匹配上的局限,同时也进一步置乱了水印图像,加强了水印图像的安全性.对宿主图像进行BEMD分解得到不同尺度下的内蕴模态函数和余量信息,并检测第1个内蕴模态函数对应图像的极值点作为水印嵌入位置.最后,依据人类视觉系统的纹理掩蔽特性,将一维水印信号按照从左至右、自上而下的顺序依次、重复嵌入到第1个内蕴模态函数对应图像的极值点中,并结合剩余内蕴模态函数及余量信息重建得到嵌入水印后的图像.水印图像的提取为该嵌入过程的逆过程.通过对多组图像进行水印嵌入,得到嵌入水印后图像的峰值信噪比均在40 dB以上;对嵌入水印后图像进行高斯噪声、椒盐噪声、大尺度剪切等攻击实验,得到提取水印图像与原始水印图像的归一化相关系数均在0.96以上.实验结果表明,嵌入水印图像具有良好的不可见性,并对高斯噪声、椒盐噪声,特别是对大尺度剪切具有较强的鲁棒性.     

一种基于DCT和Logistic Map的医学图像鲁棒多水印方法

数字医疗系统在便利了医学信息的存储、传输的同时也带来了信息安全问题, 针对医学图像的安全性提出一种适用于医学图像认证和保护的鲁棒多水印方法。通过DCT获取医学图像的视觉特征向量来进行多水印的嵌入与提取, 使用混沌加密技术对多水印进行预处理来提高水印信息的安全性, 并结合零水印概念得到可抗击常规攻击和几何攻击的水印。实验结果表明, 该方法可以有效地提取水印信息, 并且有较好的不可见性和鲁棒性。此外, 与现存的水印技术相比, 该方法不仅可以降低水印嵌入的复杂度, 而且可以提高水印嵌入的容量, 有更好的灵活性和实用性。     

BlessMark: a blind diagnostically-lossless watermarking framework for medical applications based on deep neural networks

Nowadays, with the development of public network usage, medical information is transmitted throughout the hospitals. A watermarking system can help for the confidentiality of medical information distributed over the internet. In medical images, regions-of-interest (ROI) contain diagnostic information. The watermark should be embedded only into non-regions-of-interest (NROI) regions to keep diagnostically important details without distortion. Recently, ROI based watermarking has attracted the attention of the medical research community. The ROI map can be used as an embedding key for improving confidentiality protection purposes. However, in most existing works, the ROI map that is used for the embedding process must be sent as side-information along with the watermarked image. This side information is a disadvantage and makes the extraction process non-blind. Also, most existing algorithms do not recover NROI of the original cover image after the extraction of the watermark. In this paper, we propose a framework for blind diagnostically-lossless watermarking, which iteratively embeds only into NROI. The significance of the proposed framework is in satisfying the confidentiality of the patient information through a blind watermarking system, while it preserves diagnostic/medical information of the image throughout the watermarking process. A deep neural network is used to recognize the ROI map in the embedding, extraction, and recovery processes. In the extraction process, the same ROI map of the embedding process is recognized without requiring any additional information. Hence, the watermark is blindly extracted from the NROI. Furthermore, a three-layer fully connected neural network is used for the detection of distorted NROI blocks in the recovery process to recover the distorted NROI blocks to their original form. The proposed framework is compared with one lossless watermarking algorithm. Experimental results demonstrate the superiority of the proposed framework in terms of side information.

     

New watermarking algorithm utilizing quaternion Fourier transform with advanced scrambling and secure encryption

Digital watermarking technology, as a powerful tool for copyright protection and content authentication of multimedia works, has received increasing attention, and the current image watermarking technology has developed significantly. Generally, embedding a watermark is done in grayscale images, mainly due to the fact that grayscale images are easier to process than color images, and grayscale images only contain brightness information and color-free information, in which an embedded watermark will not produce new color components. In real life, however, color images are more common than grayscale image information. To improve the security of the watermark information and the ability to embed the location and improve the security of the algorithm against a variety of attacks, this paper proposes an algorithm based on quaternion Fourier transform (QFT) with chaotic encryption and Arnold scrambling. Geometric Algebra (GA) can process color images in the form of vectors, and each component of Red,Green and Blue (RGB) should be processed separately. We utilized quaternion (which is a subalgebra of GA) and effectively completed color image processing by utilizing Fourier transform. After utilizing QFT, each component was made more secure by scrambling the pixels of the watermark and performing encryption utilizing chaotic sequencing. Different types of results utilizing Mean Square Error (MSE),Peak Signal to Noise Ratio (PSNR),Structure Similiarity Index Metric (SSIM), etc. were computed to verify the performance of our proposed algorithm and show that the robustness and security are high by utilizing our method.

     

基于向量相似度的水印模型分析

数字水印能量分析有助于平衡水印的不可视性和鲁棒性。当前数字水印嵌入能量往往通过反复实验确定。为此首先介绍了基于向量相似度的水印模型。接着定量分析了嵌入强度和密钥对峰值信噪比以及水印提取正确率的影响。最后通过仿真实验验证了理论结果：随着嵌入强度的增大,密钥对峰值信噪比和水印提取正确率影响减弱;针对特定嵌入强度存在最佳密钥子集使得水印提取正确率最大。这对于基于向量相似度的数字水印设计具有指导意义,可以从理论上计算需要嵌入水印的能量。     

A robust digital image watermarking technique using lifting wavelet transform and firefly algorithm

In this paper, an optimized and robust digital image watermarking technique based on lifting wavelet transform (LWT) and firefly algorithm is proposed. LWT is newer and faster generation of former wavelet transforms and firefly algorithm is an efficient optimizing algorithms. In current technique, base image decomposed by LWT into 4 sub bands then the first sub band separated into non overlapping blocks. After that blocks are sorted in order of descending based on standard derivation of each block. Selecting suitable blocks for special embedding process seems to be an optimization problem due to existence of a trade-off between imperceptibility and robustness. Firefly algorithm used to solve this trade-off while selecting primary blocks causes high robustness and low imperceptibility and vice versa. For improving security, Arnold transform applied to watermark and achieved scrambled image bits used as condition for embedding process. The proposed technique evaluated by variety of attacks like additive noise, average filter, median filter, sharpening filter and some other geometric and non-geometric attacks and experimental results showed its good imperceptibility and high robustness.     

基于整数小波的无损数字水印技术

提出基于整数小波的大容量数据嵌入具有无损图像恢复性能的数字水印技术。由于预先压缩灰度直方图的动态范围，因此嵌入数据后的小波反变换的灰度在0～255范围内。该文在小波域最高分辨率区的次低位平面嵌入数据，利用小波的多分辨率、解相关和高压缩率的特点,在图像中嵌入大量数据，并且使之具有视觉不敏感的特性。数据提取后图像能完全恢复。文中的例子说明这个论点是正确的。为获取更高的PSNR，提出两种修改直方图的方法，并通过具体的实验数据比较两者的效果。     

An adaptive HVS based video watermarking scheme for multiple watermarks using BAM neural networks and fuzzy inference system

An efficient reversible adaptive video watermarking scheme for multiple watermarks based on Bi-directional Associative Memory (BAM) Neural Networks and Fuzzy Inference System namely, Multi-BAM-FUZ scheme is proposed in this paper. The main goal of this paper is to design a robust video watermarking system which facilitates secure video transmission over a communication channel by maintaining a trade-off among imperceptibility, robustness and watermark capacity or payload. The BAM neural network supports creation of weight matrix (formed out of multiple images) and this matrix is embedded into the DWT uncorrelated mid frequency coefficients of all the components (Y, Cb, Cr) of every frames of the video with varying embedding strength ‘α’. This adaptive embedding strength is generated using the Fuzzy Inference System which takes HVS characteristics such as luminance, texture and edge of each frame as an input in the DWT transform. The simulations performed on various test videos demonstrate that the proposed Multi-BAM-FUZ not only outperforms other existing methods with respect to various video degradation processes, but also maintains a satisfactory image quality, robustness and payload. It is noted that, the implementation of the novel adaptive process enhances the visual quality of about 60.97 dB in terms of PSNR and 0.9998 in terms of SSIM, robustness of about nearly 1.0000 and 0.9999 in terms of Normalized Cross Correlation (NCC) value and Bit Correction Rate (BCR) respectively against various attacks. Moreover, the proposed scheme facilitates high level of payload without affecting the imperceptibility and robustness level.     

一种基于LPM和小波提升的零水印算法

大多数数字水印方法在水印嵌入的时候都是对原始图像信息作了一定的修改,这样使鲁棒性和安全性受到限制。零水印不需要修改原始图像的任何信息,有更好的透明性。本文提出了一种基于整数小波提升方案和对数极坐标映射(LPM)的零水印算法。首先将水印图像进行置乱,对载体图像进行缩放归一化,然后进行对数极坐标映射(LPM),再进行一级整数小波提升,利用分解后的低频子图和置乱后水印图像构造密图,提取时利用密图来提取水印,增强了水印的透明性和安全性。     

An adjustable-purpose image watermarking technique by particle swarm optimization

Imperceptibility, security, capacity, and robustness are among many aspects of image watermarking design. An ideal watermarking system should embed a large amount of information perfectly securely, but with no visible degradation to the host image. Many researchers have geared efforts towards developing specific techniques for variant applications. In this paper, we propose an adjustable-purpose, reversible and fragile watermarking scheme for image watermarking by particle swarm optimization (PSO). In general, given any host image and watermark, our scheme can provide an optimal watermarking solution. First, the content of a host image is analyzed to extract significant regions of interest (ROIs) automatically. The remaining regions of non-interest (RONIs) are collated for embedding watermarks by different amounts of bits determined by PSO to achieve optimal watermarking. The parameters can be adjusted relying upon user’s watermarking purposes. Experimental results show that the proposed technique has accomplished higher capacity and higher PSNR (peak signal-to-noise ratio) watermarking.     

Information hiding in medical images: a robust medical image watermarking system for E-healthcare

Electronic transmission of the medical images is one of the primary requirements in a typical Electronic-Healthcare (E-Healthcare) system. However this transmission could be liable to hackers who may modify the whole medical image or only a part of it during transit. To guarantee the integrity of a medical image, digital watermarking is being used. This paper presents two different watermarking algorithms for medical images in transform domain. In first technique, a digital watermark and Electronic Patients Record (EPR) have been embedded in both regions; Region of Interest (ROI) and Region of Non-Interest (RONI). In second technique, Region of Interest (ROI) is kept untouched for tele-diagnosis purpose and Region of Non-Interest (RONI) is used to hide the digital watermark and EPR. In either algorithm 8?×?8 block based Discrete Cosine Transform (DCT) has been used. In each 8?×?8 block two DCT coefficients are selected and their magnitudes are compared for embedding the watermark/EPR. The selected coefficients are modified by using a threshold for embedding bit a ‘0’ or bit ‘1’ of the watermark/EPR. The proposed techniques have been found robust not only to singular attacks but also to hybrid attacks. Comparison results viz-a - viz payload and robustness show that the proposed techniques perform better than some existing state of art techniques. As such the proposed algorithms could be useful for e-healthcare systems.     

Adaptive color image watermarking by the use of quaternion image moments

The first adaptive moment-based color image watermarking is presented in this work. The proposed method exploits rotation invariance, high reconstruction capability and computation accuracy of the quaternion radial moments’ (QRMs), subject to the tradeoff between robustness and imperceptibility. The current system manages to multi-embed binary logos to color images applying QRMs as information carriers. A novel adaptive system adjusts the watermark’s embedding strength (online) by taking into account image’s morphology, with respect to robustness and imperceptibility. The method manages to experimentally justify and further eliminate the attack-free phenomenon that state-of-the-art methods suffer. The simulation results justified that the proposed framework manages to highly secure its carrying information under common signal processing and geometric attacking conditions. Furthermore, the adoption of the novel adaptive process enhances the robustness and imperceptibility requirements by reducing the Bit Error Rate even by 49% and producing even 5db higher PSNR values, respectively.     

Attack resistant watermarking technique based on fast curvelet transform and Robust Principal Component Analysis

Watermarking is a technique which embeds the copyright information/identifier to provide authenticity in robust and imperceptible manner. In this paper, a hybrid watermarking technique is proposed based on combination of Fast Curvelet Tansform (FCT), Robust Principal Component Analysis (RPCA) and Singular Value Decomposition (SVD). The gray-scale watermark logo is scrambled using Generalized Arnold Transform (GAT) to enhance the robustness and security. The original image is decomposed to low rank and sparse components using RPCA; the curvelet coefficients are obtained using FCT via Unequally-Spaced Fast Fourier Transforms (USFFT) to embed the processed watermark using SVD into the color image. In curvelet transform, fewer coefficients contain the most energy, also giving optimally sparse representation of the significant image features and edges that helps in efficient recovery of the embedded watermark even after severe image degradation. The robustness and imperceptibility of the proposed technique is verified against a variety of processing operations (noise, filtering) and geometric attacks (crop, resize, projection etc.). The quantitative and visual results reveal that the watermarking technique proposed is more efficient and provides high tolerance against different geometric and image processing attacks.     

A fuzzy based ROI selection for encryption and watermarking in medical image using DWT and SVD

Nowadays secure medical image watermarking had become a stringent task in telemedicine. This paper presents a novel medical image watermarking method by fuzzy based Region of Interest (ROI) selection and wavelet transformation approach to embed encrypted watermark. First, the source image will undergo fuzzification to determine the critical points through central and final intensity along the radial line for selecting region of interest (ROI). Second, watermark image is altered to time-frequency domain through wavelet decomposition where the sub-bands are swapped based on the magnitude value obtained through logistic mapping. In the each sub-band all the pixels get swapped, results in fully encrypted image which guarantees the watermark to a secure, reliable and an unbreakable form. In order to provide more robustness to watermark image, singular values are obtained for encrypted watermark image and key component is calculated for avoiding false positive error. Singular values of the source and watermark image are modified through key component. Experimental results reveal that the proposed algorithm attains high robustness and improved security to the watermarked image against various kinds of attacks.

     

基于多尺度知识学习的深度鲁棒水印算法

针对现有基于深度学习框架的水印算法无法有效保护高维医学图像版权问题,提出一种基于多尺度知识学习的医学图像水印算法用于弥散加权图像的版权保护。首先,提出一个基于多尺度知识学习的水印嵌入网络来嵌入水印,并通过微调的预训练网络提取弥散加权图像的语义、纹理、边缘以及频域信息作为多尺度的知识特征;然后,结合多尺度的知识特征来重构弥散加权图像,并在该过程中冗余地嵌入水印,从而获得视觉上与原始图像高度相似的含水印的弥散加权图像;最后,提出一个基于金字塔特征学习的水印提取网络,并通过在含有水印的弥散加权图像的不同尺度的上下文中学习水印信号的分布相关性来提高算法的鲁棒性。实验结果表明,所提算法重构出的含水印图的平均峰值信噪比（PSNR）达到57.82 dB。由于弥散加权图像在转换为弥散张量图像时需满足一定的弥散性特征,所提算法仅8个像素点的主轴方向偏转角大于5°,且这8个像素点均不在图像的感兴趣区域。此外,该算法所得图像的各项异性（FA）以及平均弥散率（MD）都接近为0,完全满足临床诊断的要求;且面对裁剪强度小于0.7,旋转角度小于15°等常见的噪声攻击,该算法的水印正确率达到95%以上,能有效保护弥散...     

使用四叉树分割进行自适应空域隐写

目的 针对自适应隐写术可有效避免对载体敏感区大量修改的关键问题,为间接提高安全性和增大隐写容量,在四叉树分割和自适应像素对匹配（APPM）的基础上提出一种自适应空域隐写术。方法 首先该方法以图像块的纹理复杂度作为一致性测度并且设置图像块大小为判别准则进行图像分割,根据四叉树分割结果中面积较小的图像块属于复杂区域,较大的属于平滑区域,按照图像块面积大小将图像分成由高复杂、中复杂、低复杂三大区域构成。其次嵌密方式采用APPM,根据密信容量和载体图像选择进制数B。最后,为了保证安全性和提高容量,优先选择高复杂区嵌入不低于B进制的密信,在中复杂区进行B进制的密信嵌入,在低复杂区选择不高于B进制的密信嵌入。结果 为了验证提出的方法,选8幅经典图作为实验,在嵌入率1.92 bit/pixel的情况下,与已有PVD系列算法和DE算法相比具有更高的PSNR值,PSNR值高达48 dB。此外与APPM算法比较,在嵌入率2.5 bit/pixel情况下,该算法的平均KL距离相比传统APPM算法减小了25.37%,平均一阶Markov安全指标值相比传统APPM算法减小了12.11%,对应的平均PSNR值相比传统APPM算法提高0.43%,在嵌入率1.5 bit/pixel情况下,该算法的平均KL距离相比传统APPM算法减小了37.84%,平均一阶Markov安全指标值相比传统APPM算法减小了26.61%,对应的平均PSNR值相比传统APPM算法提高1.56%。此外,从RSP图库中随机选1 000幅图作为数据集,在嵌入率0.5,0.6,0.7,0.8,0.9和1.0 bit/pixel条件下,结合SPAM特征和SVM分类器的最小平均错误率均高于LSB系列经典算法和APPM算法。结论 1）考虑了人类视觉系统对图像不同区域的敏感性不同,通过对图像进行四叉树分割预处理,优先选择非敏感区进行隐写,保证了一定的安全性要求,低嵌入率下抗SPAM检测和统计不可见性方面比较有优势。2）在四叉树分割中,对于隐写前后图像的四叉树分割结果不同的异常情况,采用一种图像块纹理复杂度调整方案,保证了密信正确完整提取。3）利用了APPM算法的大容量特性,可以隐写嵌入率大于1 bit/pixel的密信,比较适用于大容量的密信隐写,而且可以嵌入任意进制的密信,最大程度地减少嵌入失真,此外,进行了四叉树分割预处理,在安全性方面优于传统APPM算法。     

Optimized gray-scale image watermarking using DWT–SVD and Firefly Algorithm

This paper presents an optimized watermarking scheme based on the discrete wavelet transform (DWT) and singular value decomposition (SVD). The singular values of a binary watermark are embedded in singular values of the LL3 sub-band coefficients of the host image by making use of multiple scaling factors (MSFs). The MSFs are optimized using a newly proposed Firefly Algorithm having an objective function which is a linear combination of imperceptibility and robustness. The PSNR values indicate that the visual quality of the signed and attacked images is good. The embedding algorithm is robust against common image processing operations. It is concluded that the embedding and extraction of the proposed algorithm is well optimized, robust and show an improvement over other similar reported methods.