基于DWT-SVD鲁棒盲水印算法研究

本文通过对小波变换与奇异值分解的研究,实现一种基于离散小波变换和奇异值分解(DWT-SVD)的奇偶量化嵌入水印算法,可实现水印盲提取.为解决水印安全性问题,使用Arnold变换对水印进行加密;在传统离散小波变换基础上,进行奇异值分解,利用图像的奇异值良好的稳定性,提高图像的鲁棒性;在图像奇异值基础上,进行奇偶量化嵌入和...     

基于SVR的混合域鲁棒音频水印算法

对于常见的基于离散小波变换-奇异值分解的水印算法应对常见的攻击鲁棒性较差的情况,提出一种基于奇异值比(Singular Value Ratio,SVR)的混合域音频水印算法.先将音频分帧,利用音频特性选择适合水印嵌入的帧,然后对水印嵌入帧进行离散小波变换和离散余弦变换,将离散余弦变换系数分为4段,选取中频系数进行奇异值...     

基于奇异值分解的灰度水印算法

提出了一种基于离散小波变换和奇异值分解的灰度水印算法.首先在嵌入前对水印做Arnold置乱处理,然后对置乱后的水印图像及其原图像进行离散小波变换分解,同时保留小波分解后水印的高频系数,并在水印检测过程中作为密钥使用.最后对原图像小波变换后的中低频系数进行奇异值分解(SVD),并把相应的水印嵌入其中.实验结果表明,上述算法能够经受住剪切、噪声、滤波、压缩等处理,具有很强的鲁棒性.     

离散小波变换和奇异值分解相融合的彩色图像水印算法

为加强数字多媒体的版权保护,提出了一种结合离散小波变换和奇异值分解相融合的彩色图像水印算法(DWT-SVD).首先对彩色数字载体图像进行小波分解,并对其小波系数进行奇异值分解;然后对水印信息采用Arnold进行置乱,并进行奇异值分解;最后将水印信息的奇异值嵌入到彩色图像的小波系数奇异值中,并对水印嵌入强度进行调节.仿真结果表明,DWT-SVD可以检测到完整的水印信息,具有良好的不可见性,对各种攻击具有较强的鲁棒性.     

DWT和SVD相融合的彩色图像水印算法北大核心

为加强数字多媒体的版权保护,提出了一种结合离散小波变换和奇异值分解相融合的彩色图像水印算法(DWTSVD)。首先对彩色数字载体图像进行小波分解,并对其小波系数进行奇异值分解;然后对水印信息采用Arnold进行置乱,并进行奇异值分解;最后将水印信息的奇异值嵌入到彩色图像的小波系数奇异值中,并对水印嵌入强度进行调节。仿真结果表明,DWT-SVD可以检测到完整的水印信息,具有良好的不可见性,对各种攻击具有较强的鲁棒性。     

基于DWT-DFT和SVD域的盲水印算法

提出了一种基于离散小波变换、离散傅里叶变换和奇异值分解相结合的盲水印算法。该算法对原始图像进行一级离散小波变换后选择低频子带图像作分块离散傅里叶变换,然后对分块离散傅里叶变换的幅度谱进行奇异值分解,选择最大奇异值并采用量化嵌入方法实现水印的嵌入和盲提取。为了提高算法对旋转攻击的鲁棒性,采用基于Radon变换的检测算法对待检测图像进行旋转校正。实验结果表明,该算法对一些常规攻击和几何攻击都具有较强的鲁棒性。     

一种基于DWT_SVD的抗几何攻击彩色图像水印算法

针对传统离散小波变换(DWT)水印算法不能较好地抵抗几何攻击的缺点,提出了一种基于离散小波变换(DWT)和奇异值分解(SVD)相结合的彩色图像水印新算法。首先对原始彩色载体图像进行RGB三基色分解,然后进行离散小波变换,再选取四个子块的四分之一重构成新子块,并进行二次离散小波变换,最后对其低频部分进行奇异值分解嵌入水印信息,得到嵌入水印的彩色图像。实验结果表明,该算法能够较好地抵抗诸如高斯噪声、椒盐噪声、压缩等常规攻击,并对大角度旋转、任意角度旋转、剪切加旋转等几何攻击也表现出了较强的鲁棒性,其总体性能明显优于传统的DWT水印算法。     

一种基于DWT与SVD的数字图像水印算法

利用小波变换和矩阵奇异值的固有特性,提出了一种基于小波变换和奇异值分解的数字图像水印算法.算法对原始载体图像进行小波变换和奇异值分解;对水印图像进行Arnold变换和奇异值分解;把分解后的水印信息嵌入到分解后的原始载体图像中,再进行相应的变换处理,得到嵌有水印的图像.实验结果表明,该算法具有良好的安全性和鲁棒性.     

一种基于小波变换与奇异分解的图像水印算法

提出一种基于离散小波变换(Discrete Wavelet Transform,DWT)与奇异值分解(Singular Value Decomposition,SVD)相结合的数字水印算法。该算法将原始图像的小波子图进行奇异值分解,将灰度水印图像进行Arnold变换以及扰乱加密,再进行分块离散余弦变换(Discrete Cosine Transform,DCT),将变换后的系数分类嵌入到相应的奇异值中。实验仿真表明,这种方法能抗大多数图像处理攻击,具有良好的鲁棒性。     

一种基于DWT-DCT-SVD的鲁棒性音频水印算法

针对在基于DWT-DCT进行数字音频水印嵌入,在已嵌入水印的音频受到噪声干扰、低通滤波、重采样等常见的攻击时,其鲁棒性差以及安全性弱的情况.提出了一种新的的盲水印嵌入算法.该算法对原始音频信号完成分帧预处理后,对每帧信号应用离散小波变换(DWT),选取三级低频分量进行离散余弦变换(DCT),先把得到的一维信号平均分解为两个片段,然后进行奇异值分解(SVD),根据奇异值的特性将水印信息嵌入到奇异矩阵.在水印图像的预处理上,采用了以Arnold变换为基础,将水印图像降维,方便水印信息的嵌入.并且通过添加密匙来提升数字音频水印的安全性.使用5个不同种类的音乐类型,进行仿真实验.实验结果表明:其误码率(BER)在0.0896以下,相关系数(NC)在0.9708以上.本算法对噪声干扰、低通滤波、重采样、重量化、剪切、压缩等常见的攻击方法具有良好的鲁棒性.     

一种新的自适应数字水印算法

为了提高数字水印抗击各种图像攻击的性能和保持图像的稳健性和不可见性,提出了一种基于离散小波变换(DWT),SVD(singular value decomposition)奇异值分解水印图像和原始载体图像的离散余弦变换(DCT)的自适应水印嵌入算法,主要是将水印图像的两次小波变换后的低频分量潜入到原始图像分块经过SVD分解的S分量矩阵中,同时根据图像的JPEG压缩比的不同计算各个图像块的水印调节因子。实验证明该算法在抗击JPEG压缩、中值滤波、加噪等均具有很好的鲁棒性,嵌入后的图像的PSNR达到38,具有良好的视觉掩蔽性     

基于图变换和DWT-SVD的鲁棒图像水印算法北大核心CSCD

针对图像水印算法在攻击强度较大时鲁棒性差的问题,提出了一种基于图变换(graph-based transform,GBT)、离散小波变换(discrete wavelet transform,DWT)和奇异值分解(singular value decomposition,SVD)的鲁棒图像水印算法。首先对载体图像进行不重叠分块处理,挑选出像素方差值较高的子块进行DWT得到其低频系数矩阵,然后对低频系数矩阵依次进行GBT和SVD得到奇异值矩阵,最后将水印信息嵌入到奇异值矩阵的最大奇异值中。实验结果表明,Pirate图像结构相似度(structural similarity,SSIM)达到0.97以上时,本文算法能有效抵抗噪声、滤波、JPEG压缩、剪切和交换行列等攻击,归一化互相关系数(normalization coefficient,NC)值均在0.9以上。     

Efficient video watermarking based on singular value decomposition in the discrete wavelet transform domain

This paper presents an efficient, robust, and imperceptible video watermarking technique based on singular value decomposition (SVD) performed in the Discrete Wavelet Transform (DWT) domain. In the proposed DWT-based SVD video watermarking method, the video frames are transformed with the DWT using two resolution levels. The high frequency band HH and the middle frequency bands LH and HL are SVD transformed and the watermark is hidden in them. The proposed DWT-based SVD video watermarking method is characterized by two improvements: (1) a cascade of two powerful mathematical transforms; the Discrete Wavelet Transform (DWT)-based SVD using additive method, and (2) an error correction code is applied and embeds the watermark with spatial and temporal redundancy. The aim of these improvements is to increase robustness against attacks based on video characteristics and the robustness against image processing attacks, realize high security level, protect the watermark against bit errors and obtain good perceptual quality. The proposed DWT-based SVD video watermarking method has been tested in the presence of video and image processing attacks and experimental results proved that the proposed DWT-based SVD video watermarking method survives attacks based on video characteristics and image processing techniques.     

CT scan contrast enhancement using singular value decomposition and adaptive gamma correction

We propose in this paper a new enhancement algorithm dedicated to dark computed tomography (CT) scan based on discrete wavelet transform with singular value decomposition (DWT–SVD) followed by adaptive gamma correction (AGC). Discrete wavelet transform (DWT) is considered to decompose the input dark CT image in four sub-bands. Singular value decomposition (SVD) is used in order to compute the corresponding singular value matrix of low–low (LL) sub-band image. The enhanced LL sub-band is determined by scaling the singular value matrix of original LL sub-band by an adequate correction factor, followed by inverse SVD. For a further contrast improvement, the new enhanced LL sub-band image is processed using an AGC algorithm. Finally, the obtained LL sub-band image undergoes inverse DWT together with the unprocessed sub-bands to generate the final enhanced image. This proposed method has the advantage of being fully automatic and could be applied for dark input images with either low or moderate contrast. Different dark CT images are considered to compare the performance of our proposed method to three other enhancement techniques using both objective and subjective assessments. Simulation results show that our proposed algorithm consistently produces good contrast enhancement, with best brightness and edges details conservation and with minimum added distortions to the enhanced CT images.     

基于DWT-SVD的大容量音频水印算法

在音频水印领域,嵌入大量水印而不影响宿主音 频的听觉质量,同时具有良好的鲁棒 性,仍然是一项具有挑战的工作。针对这一问题,本文提出了一种大容量,透明,鲁棒的音 频水印算法。首先对音频应用2级离散小波变换(DWT),并选取低频分量作奇异值分解(SV D),然后将水印嵌入在奇异值矩阵的非对角线元素中,可同时提高算法的透明性和嵌入容 量。另外,利用汉明码编码提升水印的鲁棒性和安全性。仿真实验结果表明,所提算法在平 均信噪比37.75 dB的情况下,可以达到5512 bps 的嵌入容量,对噪声添加、滤波、剪切、压缩等各种信号处理攻击具有良好的鲁棒性。     

A transcoding-resistant video watermarking algorithm based on corners and singular value decomposition

The singular value decomposition (SVD) mathematical technique provides an elegant method for extracting algebraic features form an image. When a small change is added to singular values, great variance of image doesn’t occur, and singular values in an image are less affected if general image processing is performed. Because singular value matrix of an image has good stability, the watermark can be embedded to this matrix without causing large variation in the stego-image. The reason of causing block effects and flicker in the traditional watermarked video using SVD is firstly analyzed in this paper. Based on the feature of SVD and that human eyes are not sensitive to the changes in corner area of each frame of video, we embed watermark into blocks with corner inside using quantization index modulation. We analyze the validity of the proposed algorithm about synchronizing error, block effects, and flicker. The experiment shows that the proposed approach has an excellent robustness against transcoding and some normal attacks, such as adding noise, re-encoding and so on without causing any block effects and flicker. The result also shows that the correct rate of extracting watermark can achieve 98 % per second.     

An effective SVD-based image tampering detection and self-recovery using active watermarking

In this paper, an effective tamper detection and self-recovery algorithm based on singular value decomposition (SVD) is proposed. This method generates two distinct tamper detection keys based on the singular value decomposition of the image blocks. Each generated tamper detection and self-recovery key is distinct for each image block and is encrypted using a secret key. A random block-mapping sequence and three unique optimizations are employed to improve the efficiency of the proposed tamper detection and the robustness against various security attacks, such as collage attack and constant-average attack. To improve the proposed tamper localization, a mixed block-partitioning technique for 4×4 and 2×2 blocks is utilized. The performance of the proposed scheme and its robustness against various tampering attacks is analyzed. The experimental results demonstrate that the proposed tamper detection is superior in terms of tamper detection efficiency with a tamper detection rate higher than 99%, security robustness and self-recovery image quality for tamper ratio up to 55%.