Robust Quantzation Index Modulation VIA Adaptive Watermarking

In this paper,we suggest an adaptive watermarkingmethod to improve both transparence and robustnessof quantization index modulation(QIM)scheme.Instead of a fixed quantization step-size,we apply astep-size adapted to image content in each 8×8block to make a balance of robust extraction andtransparent embedding.The modified step-size isdetermined by contrast masking thresholds ofWatson’s perceptual model.From a normalizedcrossed-correlation value between the original watermarkand the detected watermark,we could observethat our method is robust to attacks of additivewhite Gaussian noise(AWGN),Salt and Peppernoise and Joint Photographic Experts Group(JPEG)compression than the original QIM.By taking intoaccount the contrast insensitivity and visible thresholdsof human visual system,the suggested improvementachieves a maximum embedding strength andan appropriate quantization step-size which is consistentwith local values of a host signal.

Improving Video Watermarking through Galois Field GF(2^(4)) Multiplication Tables with Diverse Irreducible Polynomials and Adaptive Techniques

Video watermarking plays a crucial role in protecting intellectual property rights and ensuring content authenticity.This study delves into the integration of Galois Field(GF)multiplication tables,especially GF(2^(4)),and their interaction with distinct irreducible polynomials.The primary aim is to enhance watermarking techniques for achieving imperceptibility,robustness,and efficient execution time.The research employs scene selection and adaptive thresholding techniques to streamline the watermarking process.Scene selection is used strategically to embed watermarks in the most vital frames of the video,while adaptive thresholding methods ensure that the watermarking process adheres to imperceptibility criteria,maintaining the video's visual quality.Concurrently,careful consideration is given to execution time,crucial in real-world scenarios,to balance efficiency and efficacy.The Peak Signal-to-Noise Ratio(PSNR)serves as a pivotal metric to gauge the watermark's imperceptibility and video quality.The study explores various irreducible polynomials,navigating the trade-offs between computational efficiency and watermark imperceptibility.In parallel,the study pays careful attention to the execution time,a paramount consideration in real-world scenarios,to strike a balance between efficiency and efficacy.This comprehensive analysis provides valuable insights into the interplay of GF multiplication tables,diverse irreducible polynomials,scene selection,adaptive thresholding,imperceptibility,and execution time.The evaluation of the proposed algorithm's robustness was conducted using PSNR and NC metrics,and it was subjected to assessment under the impact of five distinct attack scenarios.These findings contribute to the development of watermarking strategies that balance imperceptibility,robustness,and processing efficiency,enhancing the field's practicality and effectiveness.

Adaptive Image Digital Watermarking with DCT and FCM

A novel adaptive digital image watermark algorithm is proposed. Fuzzy c-means clustering （FCM） is used to classify the original image blocks into two classes based on several characteristic parameters of human visual system （HVS）. One is suited for embedding a digital watermark, the other is not. So the appropriate blocks in an image are selected to embed the watermark. The wetermark is embedded in the middle-frequency part of the host image in conjunction with HVS and discrete cosine transform （DCT）. The maximal watermark strength is fixed according to the frequency masking. In the same time, for the good performance, the watermark is modulated into a fractal modulation array. The simulation results show that we can remarkably extract the hiding watermark and the algorithm can achieve good robustness with common signal distortion or geometric distortion and the quality of the watermarked image is guaranteed.

MODIFIED QUANTIZATION INDEX MODULATION WATERMARKING ADAPTIVE TO CONTRAST MASKING THRESHOLDS

In this paper,we suggest an adaptive watermarking method to improve both transparence and robustness of quantization index modulation(QIM) scheme. Instead of a fixed quantization step-size,we apply a step-size adapted to image content in each 8×8 block to make a balance of robust extraction and transparent embedding.The modified step-size is determined by contrast masking thresholds of Watson’s perceptual model.From a normalized crossed-correlation value between the original watermark and the detected watermark,we could observe that our method is robust to attacks of additive white Gaussian noise(AWGN),Salt and Pepper noise and Joint Photographic Experts Group(JPEG) compression than the original QIM.By taking into account the contrast insensitivity and visible thresholds of human visual system,the suggested improvement achieves a maximum embedding strength and an appropriate quantization step-size which is consistent with local values of a host signal.

LKAW: A Robust Watermarking Method Based on Large Kernel Convolution and Adaptive Weight Assignment

Robust watermarking requires finding invariant features under multiple attacks to ensure correct extraction.Deep learning has extremely powerful in extracting features,and watermarking algorithms based on deep learning have attracted widespread attention.Most existing methods use 3×3 small kernel convolution to extract image features and embed the watermarking.However,the effective perception fields for small kernel convolution are extremely confined,so the pixels that each watermarking can affect are restricted,thus limiting the performance of the watermarking.To address these problems,we propose a watermarking network based on large kernel convolution and adaptive weight assignment for loss functions.It uses large-kernel depth-wise convolution to extract features for learning large-scale image information and subsequently projects the watermarking into a highdimensional space by 1×1 convolution to achieve adaptability in the channel dimension.Subsequently,the modification of the embedded watermarking on the cover image is extended to more pixels.Because the magnitude and convergence rates of each loss function are different,an adaptive loss weight assignment strategy is proposed to make theweights participate in the network training together and adjust theweight dynamically.Further,a high-frequency wavelet loss is proposed,by which the watermarking is restricted to only the low-frequency wavelet sub-bands,thereby enhancing the robustness of watermarking against image compression.The experimental results show that the peak signal-to-noise ratio(PSNR)of the encoded image reaches 40.12,the structural similarity(SSIM)reaches 0.9721,and the watermarking has good robustness against various types of noise.

A Novel Color Image Watermarking Method with Adaptive Scaling Factor Using Similarity-Based Edge Region

This study aimed to deal with three challenges:robustness,imperceptibility,and capacity in the image watermarking field.To reach a high capacity,a novel similarity-based edge detection algorithm was developed that finds more edge points than traditional techniques.The colored watermark image was created by inserting a randomly generated message on the edge points detected by this algorithm.To ensure robustness and imperceptibility,watermark and cover images were combined in the high-frequency subbands using Discrete Wavelet Transform and Singular Value Decomposition.In the watermarking stage,the watermark image was weighted by the adaptive scaling factor calculated by the standard deviation of the similarity image.According to the results,the proposed edge-based color image watermarking technique has achieved high payload capacity,imperceptibility,and robustness to all attacks.In addition,the highest performance values were obtained against rotation attack,to which sufficient robustness has not been reached in the related studies.

A Binary Images Watermarking Algorithm Based on Adaptable Matrix

A watermarking algorithm of binary images using adaptable matrix is presented. An adaptable matrix is designed to evaluate the smoothness and the connectivity of binary images. The watermark is embedded according to the adaptable matrix in this algorithm. In the proposed watermarking algorithm, each image block implements a XOR operation with the binary adaptable matrix, which has the same size with the image block, and in order to embed the watermark data, a multiplication operation are also implemented with the weight matrix. The experimental results show that proposed scheme has a good performance.

An optimal adaptive quantization index modulation watermarking algorithm

A novel adaptive watermarking algorithm in discrete wavelet transform （DWT） based on quantization index modulation （QIM） technique is presented. The host image is decomposed into wavelet subbands, and then the approximation subband is divided into non-overlapping small embedding blocks. The secret watermark bit is embedded into singular value vector of each embedding block by applying QIM. To improve the invisibility and robustness of watermarking system, the quantization step for each embedding block is set by combining statistical model with particle swarm optimization （PSO） algorithm. The experimental results show that the proposed algorithm not only preserves the high perceptual quality, but also effectively stands against joint photographic experts group （JPEG） compression, low-pass filtering, noise addition, scaling, and cropping attacks, etc. The comparison analysis demonstrates that our scheme has better performance than the previously reported watermarking algorithms.

A novel hybrid cryptosystem based on DQFrFT watermarking and 3D-CLM encryption for healthcare services

Quaternion algebra has been used to apply the fractional Fourier transform(FrFT)to color images in a comprehensive approach.However,the discrete fractional random transform(DFRNT)with adequate basic randomness remains to be examined.This paper presents a novel multistage privacy system for color medical images based on discrete quaternion fractional Fourier transform(DQFrFT)watermarking and three-dimensional chaotic logistic map(3D-CLM)encryption.First,we describe quaternion DFRNT(QDFRNT),which generalizes DFRNT to handle quaternion signals effectively,and then use QDFRNT to perform color medical image adaptive watermarking.To efficiently evaluate QDFRNT,this study derives the relationship between the QDFRNT of a quaternion signal and the four components of the DFRNT signal.Moreover,it uses the human vision system's(HVS)masking qualities of edge,texture,and color tone immediately from the color host image to adaptively modify the watermark strength for each block in the color medical image using the QDFRNT-based adaptive watermarking and support vector machine(SVM)techniques.The limitations of watermark embedding are also explained to conserve watermarking energy.Second,3D-CLM encryption is employed to improve the system's security and efficiency,allowing it to be used as a multistage privacy system.The proposed security system is effective against many types of channel noise attacks,according to simulation results.

AN ADAPTIVE DIGITAL IMAGE WATERMARK ALGORITHM BASED ON GRAY-SCALE MORPHOLOGY

An adaptive digital image watermark algorithm with strong robustness based on gray-scale morphology is proposed in this paper.The embedded strategies include:The algorithm seeks and extracts adaptively the image strong texture regions.The algorithm maps the image strong texture region to the wavelet tree structures, and embeds adaptively watermark into the wavelet coefficients corresponding to the image's strong texture regions.According to the visual masking features, the algorithm adjusts adaptively the watermark-embedding intensity.Experimental results show the algorithm is robust to compression, filtering, noise as well as strong shear attacks.The algorithm is blind watermark scheme.The image strong texture region extraction method based on morphology in this algorithm is simple and effective and adaptive to various images.

基于AKAZE算子的抗翻拍自适应鲁棒性水印

针对现有抗翻拍攻击水印的鲁棒性不足以抵抗新型翻拍攻击且透明性不佳等问题,引入自适应思想,提出一种基于AKAZE算子的自适应水印算法。首先利用AKAZE算子定位出关键点,随后根据关键点间的距离与对图像边框的距离对关键点做初步的筛选,然后构建筛选后关键点邻域熵值、水印嵌入强度与嵌入前后的平均相似度三者之间的映射,构建完映射后可仅根据图像块的熵值自适应筛选关键点,并得到二次筛选后关键点邻域合适的嵌入率,最后在筛选后的关键点邻域中利用奇异值分解进行水印嵌入。实验结果表明,该水印算法在保持了良好的不可见性的同时具有极佳的鲁棒性,其性能较现有抗翻拍攻击水印算法有显著提高。

基于伪Zernike矩与SURF特征的自适应水印算法

针对目前多数图像水印算法水印的嵌入区域固定不变带来的安全性问题,且水印的抗旋转攻击能力弱,提出一种基于伪Zernike矩和SURF的自适应水印算法。首先,利用SURF(Speed Up Robust Features)算法对图像进行特征提取,然后采用RANSAC(Random Sample Consensus)算法筛选出稳定的特征点,根据特征点位置构建合适的水印嵌入区域。最后,采用SWT变换和SVD分解将水印信息嵌入在构造区域内。利用伪Zernike矩估计旋转角度对图像进行旋转校正。实验结果表明,该水印算法可以有效地抵抗旋转攻击,水印的安全性得到提高。

一种小波变换域的自适应视频水印算法

稳健性是数字水印算法的主要问题之一 .根据视觉特点和信号特性实现水印分量的自适应嵌入是提高水印稳健性的有效途径 .本文提出了一种基于小波变换域的自适应视频水印算法 .水印根据 2 D小波系数的特点嵌入在低频子带系数中 ,以获得较好的稳健性 .为了在保证不可见性的前提下尽可能提高水印分量的强度 ,本文提出根据物体的运动和视频信号内容的纹理复杂度将低频子带中的系数进行分类 ,根据分类结果 ,自适应地调整嵌入水印的强度 .实验结果表明 :嵌入水印对多种攻击 ,如加性Gaussian噪声、高压缩比的MPEG 2压缩编码、时域抽样和丢帧。

基于人类视觉系统的自适应水印嵌入算法

为了保证水印算法的良好性能 ,在许多文献中提出自适应水印技术 .但是 ,大多数算法根据单一参数对图像块进行分类 ,无法实现最优嵌入 .为此 ,提出了一种新颖的基于DCT变换域的自适应数字水印嵌入算法 .该算法首先将原始图像块按照图像块的多个特性参数分成不同的类 ,在嵌入过程中考虑到人类视觉系统 (HVS)的特点 ,在不同类的块中嵌入不同的水印能量 ,从而使算法具有自适应能力 .仿真实验表明 ,该算法对常见的一些数字图像处理操作具有较强的鲁棒性 。

彩色图像超复数空间的自适应水印算法

针对彩色载体图像,本文提出了一种超复数频域的自适应水印算法,它首先对彩色载体图像进行快速超复数傅氏变换,在超复数频谱实部选择合适频段的基础上,再利用人类视觉系统对彩色载体图像的纹理、边缘和亮度的掩蔽特性,对选择的频段赋予不同的掩蔽强度而嵌入水印,从而在超复数频域内实现了一种彩色载体图像自适应的水印算法.实验结果表明,通过彩色图像的自适应掩蔽,大大提高了超复数频域水印算法的不易感知性和鲁棒性,且抗攻击性能也优于无自适应掩蔽的超复数频域水印算法;和现有文献的比较结果验证了本算法的这些优越性.

基于内容的离散余弦变换域自适应遥感图像数字水印算法

提出一种适于遥感图像知识产权保护和机密信息传递的离散余弦变换域自适应数字水印嵌入算法,该算法能够通过数字水印置乱、嵌入位置自适应选取、嵌入深度智能调节等措施,将二值水印图像信息安全地嵌入到遥感图像(纹理区)的离散余弦变换域中高频系数内。实验结果表明:该遥感图像数字水印算法不仅具有较好的透明性,而且对诸如叠加噪声J、PEG压缩、平滑滤波、几何剪切、图像增强、马赛克等攻击均具有较好的抗差性,整体性能优于Ho等提出的数字水印嵌入方案。

基于三维DCT的彩色图象自适应水印算法

本文提出了一种基于 3D DCT的彩色图象自适应水印算法 .证实了RGB彩色图象的 3D DCT比 2D DCT具有更好的能量汇聚性质并因此具有更大的感觉容量 ,从而允许嵌入更强的水印信号 .在此基础上 ,提出了利用人眼彩色视觉特性来自适应控制水印嵌入强度的方法 .实验证明该算法较好地平衡了隐形水印的不可见性和稳健性之间的矛盾 ,所隐藏的水印对常规性攻击 ,如JPEG压缩、加性噪声、图象滤波、彩色变化和亮度 /对比度变化等 。

小波用于基于遥感影像特征的自适应二维盲水印算法

文章提出了一个有效的基于遥感影像特征的自适应二维盲水印算法。该算法使用灰度图像作为水印,将水印灰度图像进行Arnold置乱加密和小波压缩后,利用相邻特征平均值和奇偶判决法嵌入遥感影像的二阶小波变换域中所选择的子带上,且水印检测不需要原始遥感影像。攻击测试和实验结果表明,该算法具有较好的透明性,强壮性,以及水印检测结果准确,算法复杂度低等优点,对如JPEG有损压缩、中值滤波、附加噪声、伸缩、裁剪、旋转、几何变换、Stirmark攻击等各种影像处理的攻击都具有较强的鲁棒性;且嵌入水印后基本不会影响遥感影像的边缘检测和分类等一些应用。

DCT变换域盲图像水印的自适应检测

检测时无需原始图像的盲数字水印是实用的数字作品版权保护系统的关键技术之一．基于图像ＤＣＴ交流系数的广义高斯分布模型，推导并实现了一种有效的自适应盲图像水印检测器．通过计算渐进相对效率证明了该检测器具有较高的检测效率．实验结果表明该检测器具有良好的鲁棒性，优于Ｂａｒｎｉ的线性相关检测器．

一种基于DFT的DEM自适应数字水印算法

通过对DEM数据进行分块傅里叶变换和频谱分析,结合人类视觉系统和DEM数据特征,自适应地确定水印嵌入位置,将水印信息以加性法则嵌入到傅里叶低频系数的幅值上,然后对DEM数据进行分块傅里叶逆变换,得到含水印信息的DEM数据。实验结果表明,该算法不仅具有很好的透明性,而且对DEM数据的精度影响较小,能够满足一定的应用要求,具有良好的抗噪能力。