基于多规则小波变换的视频水印加密算法研究

通过对视频嵌入水印的安全性和鲁棒性的分析,采用了一种基于多规则小波变换的视频水印嵌入与提取算法.该算法首先对水印图像进行置乱加密增强其安全性,其次对视频帧和水印图像分别进行多层小波变换,最后根据不同的小波系数进行多规则水印嵌入.算法不仅充分利用了小波变换的多分辨特性,而且兼顾了水印的不可感知性和视频帧的鲁棒性.实验结果表明,该算法对高斯噪声、几何失真和压缩等具有良好的安全性和鲁棒性.     

基于小波变换和神经网络的视频水印算法

针对视频版权的保护提出了一种基于三维小波变换和RBF神经网络的视频水印算法。本算法采用二值图像作为水印,对水印图像进行随机置乱预处理以增强其安全性能;对宿主视频进行视频分割,并分别对得到的各序列做三维DWT变换;把水印嵌入到经过三维变换的低频子带中,在水印提取过程中,结合RBF神经网络模型,而不需要原始图像,快速有效提取出水印。实验结果表明,该算法具有较强的不可见性,且针对帧压缩、旋转、滤波和比例缩放等具有良好的鲁棒性。     

基于小波域低频系数的自适应盲视频水印算法

设计了一种基于小波域低频系数的自适应盲视频水印算法,先用Arnold变换对水印图像进行置乱加密,再对原始视频进行分帧处理并提取亮度分量,将水印信息嵌入到亮度分量三层离散小波变换的低频系数中,嵌入强度由低频系数自适应地选取.实验结果表明,水印的安全性和不可感知性很好,在抵抗噪声干扰、帧删除、帧剪切以及滤波等多种攻击时具有良好的稳健性.     

基于独立分量分析的盲视频水印方案

本文提出一种新的盲视频水印方案.该方案利用独立分量分析方法根据相邻的视频帧提取相应的运动分量,并且把这些运动分量进行小波变换,采用邻近特征值平均法,将水印嵌入到运动分量中.运动分量是视频的重要特征,压缩的处理对于它的影响较小,因此可以提高鲁棒性.基于帧的运动分量的提取避免了基于块的重复性操作,小波域的水印嵌入可以将水印带来的影响分散到整个帧上,具有良好的不可见性.计算机仿真结果表明,该方法能够保证很好的视频质量,对于常见的视频处理有较好的鲁棒性,能够进行水印的盲检测,虚警概率小.     

基于三维小波变换的视频水印嵌入与盲提取算法

为了寻求有效的数字媒体保护方法,该文提出了一种在三维小波变换域内基于二值运算的数字视频水印嵌入算法。为了实现水印的获取,提出了一种相应的水印盲提取算法。水印的嵌入与提取算法每次只对4帧图像进行小波分解,不仅充分利用了小波变换良好的空时多分辨特性,而且占用内存空间少、时延低,适合视频流的在线水印嵌入和提取,并易于硬件的实时实现。实验结果表明,该文所提出的视频水印算法对高斯噪声、MPEG编码、帧平均、帧抽取和帧置乱具有良好的鲁棒性。     

基于DCT域的AVS视频盲水印算法

结合人眼的视觉特性,提出了一种基于DCT域的AVS视频编解码标准的视频盲水印算法.算法首先对水印图像进行增强的Arnold变换,得到置乱的二值水印图像;然后根据嵌入公式替换嵌入点的系数,将水印信息自适应嵌入到Ⅰ帧的DCT系数中.提取水印时不需要原始视频,可实现盲水印.实验结果表明,该算法对高斯、帧剪切、盐噪声等攻击,具有较好的稳健性和不可见性.     

利用视频帧块的高效半盲鲁棒水印算法

针对视频水印算法鲁棒性差或需过多先验信息提高鲁棒性的问题,提出利用视频帧块、KAZE特征匹配和DCT变换方法实现半盲鲁棒视频水印算法。首先,利用用户注册信息作为水印并为之产生唯一的秘钥,基于该秘钥随机产生唯一的帧块并存入数据库;然后,将帧与帧块进行KAZE特征匹配并检测出嵌入区域,进而嵌入水印;最后,将帧块与扭曲视频进行KAZE匹配修正视频各帧并提取水印。仿真试验结果显示,在半盲的前提下,本算法具有高鲁棒性、水印提取过程同步性、版权纠纷解决和非法传播追踪的优点,且具有高应用价值。     

基于粒子群优化和小波变换的视频水印算法

为了保护数字视频的版权,提出一种基于粒子群优化和小波变换的视频水印算法,首先对水印图像进行Arnold变换与Logistic混沌映射相结合的灰度置乱预处理以增强其安全性能;再利用直方图帧差法将视频流分为不同的场景,通过密钥从中选取若干场景进行三级三维小波变换;最后借助乘法嵌入方式把水印信息嵌入到小波变换域的中频部分,水印的嵌入强度则由粒子群优化算法(PSO)搜索得出.仿真实验结果表明,该算法能较好的体现水印的鲁棒性和不可见性.     

一种DCT域多重视频盲水印算法

针对多用户共享版权问题,提出了一种DCT域多重视频盲水印算法.该算法结合Amold置乱及视觉系统特性,通过自适应地调整视频画面绿色分量的DCT系数,实现了不同水印在视频载体中的嵌入.根据视频内容灵活地选择嵌入系数,将经过Arnold置乱的不同图像水印嵌入到视频画面绿色分量的DCT中低频系数里,较好地实现了多重水印在视频载体中的嵌入及盲提取.仿真实验表明,文中算法对常规视频攻击表现出了较好的稳定性,并且具有算法复杂度低及实用性强等特点.     

一种基于HVS的DCT域稳健视频水印算法

结合人类视觉系统特性及离散余弦变换理论,提出了一种基于原始视频的稳健性盲水印算法。该算法将置乱后的二值图像水印嵌入到原始视频帧绿色分量的离散余弦变换低频系数中,根据视频内容自适应地选择嵌入深度,较好地实现了水印在宿主视频中的嵌入及盲提取。实验结果表明,该视频水印算法在保证不可知性的同时对诸如Gaussian、帧剪切、Salt等攻击均具有良好的稳健性,即使在攻击强度较大的情况下仍然能够提取出较清晰的水印信号。     

基于帧间相关性的盲视频数字水印算法

提出了一种在原始视频中嵌入水印的算法。嵌入的水印由2部分组成:标志水印和信息水印。首先从一段原始视频里随机选出若干视频帧,在这些帧的像素平面亮度分量上固定位置嵌入标志水印,再根据密钥选取其他若干图像块在其离散余弦变换(DCT)直流系数中嵌入信息水印。然后在整段视频的每一小段中重复嵌入水印。提取水印时,只需从整段视频中截取足够包含完整信息水印的一小段视频,通过搜索标志水印快速地选出包含水印信息的帧。然后利用水印帧与前后相邻视频帧之间内容的高度相关性,得到嵌入水印位置像素值的估计,与包含水印信息帧相应位置做比较,提取出水印信息,实现了水印的盲提取。实验结果表明本算法能够抵抗压缩、缩放、帧删除/插入等各种攻击,具有较强的健壮性。     

Robust semi-blind video watermarking based on frame-patch matching

In this paper, we present a frame-patch matching based robust semi-blind video watermarking using KAZE feature. The KAZE feature is employed for matching the feature points of frame-patch with those of all frames in video for detecting the embedding and extracting regions. In our method, the watermark information is embedded in Discrete Cosine Transform (DCT) domain of randomly generated blocks in the matched region. In the extraction process, we synchronize the embedded region from the distorted video by using KAZE feature matching. Based on the matched KAZE feature points, RST (rotation, scaling, translation) parameters are estimated and the watermark information can be successfully extracted. Experimental results show that our proposed method is robust against geometrical attacks, video processing attacks, temporal attacks, and so on.     

基于双重水印加密和SVD的视频水印方案

针对视频水印的安全性,提出了一种基于双重水印加密和SVD的视频水印方案。该方法首先将水印图像经Arnold置乱,对置乱后的水印通过Chebyshev混沌映射进行加密,保障水印的安全性;然后,对视频关键帧进行三级小波分解,利用SVD对几何失真的不变性,将水印3次嵌入到LL3、HL3和LH3中。实验表明该方案对高斯噪声、MPEG压缩、剪切等具有较高的鲁棒性。     

Discrete Multiwavelet–Based Video Watermarking Scheme Using SURF

This paper proposes a robust, imperceptible block‐based digital video watermarking algorithm that makes use of the Speeded Up Robust Feature (SURF) technique. The SURF technique is used to extract the most important features of a video. A discrete multiwavelet transform (DMWT) domain in conjunction with a discrete cosine transform is used for embedding a watermark into feature blocks. The watermark used is a binary image. The proposed algorithm is further improved for robustness by an error‐correction code to protect the watermark against bit errors. The same watermark is embedded temporally for every set of frames of an input video to improve the decoded watermark correlation. Extensive experimental results demonstrate that the proposed DMWT domain video watermarking using SURF features is robust against common image processing attacks, motion JPEG2000 compression, frame averaging, and frame swapping attacks. The quality of a watermarked video under the proposed algorithm is high, demonstrating the imperceptibility of an embedded watermark.     

Robust Video Watermarking Using a Hybrid DCT-DWT Approach

In order to solve the limitations of the digital video watermarking algorithm, this paper proposes a new robust video watermarking algorithm using combining discrete cosine transform (DCT) and discrete wavelet transform (DWT) techniques. First of all, the video frames are randomly selected and then the DCT algorithm is applied to the selected video frames. After that, the first column of the selected video frames is scrambled using the Arnold algorithm. Furthermore, every column with 4 direct current (DC) coefficients is reshaped and transformed into four different sub-bands using the DWT technique. Next, the watermark is embedded into the approximation (LL) sub-band. The proposed algorithm is easy to carry out because it provides random frames with no special requirements for video frames. The experiment results indicate that this algorithm can resist against different kinds of watermarking attacks, such as the Gaussian filter attack and sharpen attack. In addition, it also illustrates that the proposed algorithm has a better result than some other watermarking algorithms.     

A new video watermarking algorithm based on 1D DFT and Radon transform

In this paper, we propose a new video watermarking algorithm based on the 1D DFT (one-dimensional discrete Fourier transform) and Radon transform. The 1D DFT for a video sequence generates an ideal domain, in which the spatial information is still kept and the temporal information is obtained. With detailed analysis and calculation, we choose the frames with highest temporal frequencies to embed the fence-shaped watermark pattern in the Radon transform domain of the selected frames. The adaptive embedding strength for different locations keeps the fidelity of the watermarked video. The performance of the proposed algorithm is evaluated by video compression standard H.264 with three different bit rates; geometric attacks such as rotation, translation, and aspect-ratio changes; and other attacks like frame drop, frame swap, spatial filtering, noise addition, lighting change, and histogram equalization. The main contributions of this paper are the introduction of the 1D DFT along temporal direction for watermarking that enables the robustness against video compression, and the Radon transform-based watermark embedding and extraction that produces the robustness against geometric transformations. One of the most important advantages of this video watermarking algorithm is its simplicity and practicality.     

Video watermarking using wavelet transform and tensor algebra

We present a robust, hybrid non-blind MPEG video watermarking technique based on a high-order tensor singular value decomposition and the discrete wavelet transform (DWT). The core idea behind our proposed technique is to use the scene change analysis to embed the watermark repeatedly into the singular values of high-order tensors computed form the DWT coefficients of selected frames of each scene. Experimental results on video sequences are presented to illustrate the effectiveness of the proposed approach in terms of perceptual invisibility and robustness against attacks.     

Video Watermark Using Multiresolution Wavelet Decomposition

A novel technique for the video watermarking based on the discrete wavelet transform(DWT) is present. The intra frames of video are transformed to three gray image firstly, and then the 2th-level discrete wavelet decomposition of the gray images is computed, with which the watermark W is embedded simultaneously into and invert wavelet transform is done to obtain the gray images which contain the secret information. Change the intra frames of video based on the three gray images to make the intra frame contain the secret information. While extracting the secret information, the intra frames are transformed to three gray image, 2th-level discrete wavelet transform is done to the gray images, and the watermark W‘ is distilled from the wavelet coefficients of the three gray images. The test results show the superior performance of the technique and potential for the watermarking of video.