小波域图像数字水印算法研究

【作者】 林瑞娟；

【导师】 侯德文；

【作者基本信息】 山东师范大学 ， 计算机软件与理论， 2007， 硕士

【摘要】 通信、计算机和Internet技术的飞速发展，在许多方面改变了人们的生活。基于计算机和网络的多媒体信息交换为数字产品的使用、传播提供了便利的途径，使数字作品与传统作品相比有很大的优越性，成为信息交流的一种主要方式。因特网上信息的获取达到了前所未有的深度和广度，但对多媒体作品的侵权也随之更加容易，非法复制、篡改也更加方便，极大的损害了作者及版权所有者的利益。如何有效的保护多媒体信息的版权成为信息安全领域的一个热门问题。作为信息隐藏在计算机多媒体领域的一个重要应用，数字水印技术使得人们能够在不影响多媒体产品(如数字图像、文档、视频、音频等)使用质量的前提下，将具有特定意义的标记(水印)，按照某种给定算法嵌入到媒体产品中，以实现对该产品的保护或认证。数字水印技术为多媒体版权保护提供了一个崭新的方法，近年来在国际上引起了人们极大的兴趣和注意，从而成为目前国际学术界研究的一个前沿热门方向。数字水印技术还远未成熟，许多问题亟待解决。本文着重对图像数字水印算法进行了研究，主要工作如下：1)首先介绍了数字水印的研究背景，接着比较回顾了数字水印的发展历史，并简述了数字水印的研究现状及存在的问题。2)较系统全面地论述了数字水印技术的各个方面，内容包括：数字水印定义，水印按不同标准进行的分类，数字水印的应用领域，数字水印应该具有的特征，及数字水印的通用模型，水印的常见攻击以及应对策略。3)由于本文的水印算法考虑了水印置乱预处理，所以还分别介绍了基于Arnold变换的图像置乱算法及幻方变换，并进行了实现。接着又介绍奇异值分解的简单原理。4)对小波分析理论作了简要介绍，主要包括：小波的定义、性质，小波在数字图像及其在数字水印中的应用，多分辨率分析，最后介绍了小波的实现算法—Mallat算法。5)作者提出了一种基于DWT域的小波水印算法。该算法实现了将置乱后的数字水印嵌入到原始载体图像的L级小波逼近子图中。实验证明，利用该算法嵌入的数字水印不但具有较好的不可见性，而且对图像噪声、滤波等攻击具有较好的鲁棒性。6)提出了一种基于奇异值分解的小波域水印算法，将奇异值分解的方法引入到水印嵌入过程中，嵌入的水印信号是灰度图像，嵌入和提取过程比较简单，实验结果表明，该算法对图像处理有较好的鲁棒性。更多还原

【Abstract】 With the development of communication, computer and Internet technology, humans’ lives have been changed dramatically. Based on the technology of computer and network, the multimedia information exchanges provide a convenient way for using and spreading of digital produces. This make digital products have more advantages than traditional products, and digital multimedia has become main means of information communication. While one can acquire a wide range of multimedia data through the Internet, various problems (copyright violation, illegal copying, easy forging, etc.) arises naturally that seriously harm the benefit of the author or the copyright owner. How to protect multimedia data from violation has become an important issue in information security field. As a main application of information hiding technique to multimedia copyright protection, the digital watermarking technique, which embeds an invisible signal (watermark) to the original multimedia data (image, audio, and video), has been proposed as a viable solution for the copyright protection and authentication of multimedia data in a networked environment since it makes it possible to identify the author, owner, distributor or authorized consumer of multimedia data. So it has drawn extensive attention in recent years and has become the most popular research interest.Digital watermarking is still in his infancy, and many problems remain yet to be solved. This paper addresses research of image digital watermarking algorithm. The main contributions are summarized as follows:Firstly, this paper introduces the research background, then reviews history of digital watermarking and sums up the current developing condition, and point out some problems of digital watermarking.In this paper, the author first makes an overall review on the digital watermarking techniques including the definition, characteristics, main application domains , basic features of digital watermarking. Then the general frame of digital watermarking is given. Finally, this paper introduces the attacks and countermeasures.As the processing of watermarking-scrambling is taken into account, image-scrambling algorithms such as Arnold transformation, Rubik Cube Transformation are introduced and simulated.The process of development, basic definition, multi-resolution analysis of wavelet, Mallat algorithm and its application in the image processing are introduced. An effective digital watermarking algorithm based on the Arnold permutation method is proposed in this paper. In our algorithm, the watermark is embedded to the low frequency coefficients of the L-deep wavelet domain. The experimental results demonstrated that the embedded watermark is not only invisible, but also robust against the attacks of the noise addition, filtering and so on.This paper proposes an algorithm based on singular value decomposition algorithms in wavelet domain. Embedding strategy and extraction method are very simple. The experimental results demonstrated that the watermark is fairly robust to several signal processing techniques.更多还原