基于经验模式分解的音频水印算法

针对传统基于经验模式分解(EMD)的音频水印算法鲁棒性不强的问题,提出一种基于固有模态函数(IMF)极值的盲音频水印算法.首先对音频信号进行分帧,每个音频帧经过EMD后得到IMF; 接着利用均匀量化的方法将水印信息和同步码嵌入到最后一个IMF的极值中.所提算法的数据嵌入率是46.9~50.3 b/s,且携水印音频保持了原始音频的感知质量.对携水印音频进行加噪、MP3压缩、重新采样、滤波、剪切和重采样攻击后,提取出的水印信息变化不大,算法鲁棒性较好.与时间域和小波域算法相比,提出的算法在保证高数据嵌入率的同时,可以抵抗32 kb/s的MP3压缩攻击.     

Audio watermarking in transform domain based on singular value decomposition and Cartesian-polar transformation

This paper presents an audio watermarking scheme in fast Fourier transform (FFT) domain based on singular value decomposition (SVD) and Cartesian-polar transformation (CPT). In our proposed scheme, initially the original audio is segmented into nonoverlapping frames. FFT is applied to each frame and low frequency FFT coefficients are selected. SVD is applied to the selected FFT coefficients of each frame represented in a matrix form. The highest singular values of each frame are selected and are decomposed into two components using CPT. Watermark information is embedded into each of these CPT components using an embedding function. Experimental results indicate that the proposed watermarking scheme is highly robust against various signal processing attacks. In addition, the proposed scheme has a high data payload. Moreover, it outperforms state-of-the-art audio watermarking methods in terms of imperceptibility, robustness, and data payload.     

基于ANFIS的倒谱域盲检测混沌音频水印算法

倒谱分析广泛运用于音频信号处理的很多方面,但目前研究倒谱域音频水印算法的文献很少,而且现有的水印算法大多没有实现盲检测,不利于实际运用。该文提出了一种具有较高鲁棒性的混沌音频水印算法,并通过自适应神经网络模糊推理系统(AdaptiveNeuro-FuzzyInferenceSystem,ANFIS)实现了盲检测。实验证明,该算法的水印嵌入易实现,水印检测准确性高,时间代价小,具有较强的抗攻击性和较好的不可感知性,很有实用价值。     

基于重心的抗同步攻击的音频水印算法

抗同步攻击是音频水印领域公开的难题. 相对重心是音频的一个稳定的全局特征量, 对 TSM (Time scale modification)等同步攻击不敏感. 本文提出一种基于相对重心的抗同步攻击的音频水印算法,提出的算法通过量化音频的相对重心生成水印, 生成的水印由混沌序列加密后以量化的方法嵌入载体音频三级小波近似分量均值中. 为了降低同步攻击后同步位置的连续偏移, 水印嵌入提取过程采用了均匀分帧的方法. 实验结果表明提出的算法能抵抗常规信号处理操作, 同时 能抵抗20%的TSM操作(包含音调不变TSM和重采样操作)和 1/10的抖动操作, 有很好的鲁棒性.     

稳健局部特征非下采样小波域数字水印

目的 基于数字水印技术的音乐作品版权保护是学术界的研究热点之一,多数数字音频水印方案仅仅能够对抗简单的常规信号处理,无法有效抵抗破坏性较强的一般性去同步攻击。为此,提出了一种基于稳健局部特征的非下采样小波域数字水印算法。方法 利用非下采样小波域平滑梯度检测算子从载体音频中提取稳定的音频特征点,结合数字音频样本响应确定局部特征音频段,采用量化调制策略将数字水印信号重复嵌入局部特征音频段中。结果 选取4段典型的采样频率为44.1 kHz、量化精度为16 bit、长度为15 s的单声道数字音频信号作为原始载体进行测试,并与经典算法在不可感知性和鲁棒性两方面进行对比。结果表明,本文算法在含水印音频与原始载体音频间的信噪比平均提升了5.7 dB,同时常规攻击和去同步攻击下的平均检测率分别保持在0.925和0.913,高于大多数传统算法,表明了本文算法具有较好的不可感知性。在常规信号处理（MP3压缩、重新量化、重新采样等）和去同步攻击（幅度缩放、随机剪切、音调伸缩、DA/AD转换、抖动等）方面均具有较好的鲁棒性。结论 本文利用描述能力强且性能稳定的平滑梯度刻画局部数字音频性质,提出一种基于平滑梯度的非下采样小波域音频特征点提取方法,有效解决了音频特征点稳定性差且分布极不均匀的缺点,提高了数字音频水印对音调伸缩、随机剪切、抖动等攻击的抵抗能力。     

频谱嫡特征识别的抗去同步鲁棒性MP3水印算法

提出了一种鲁棒的、将离散余弦系数(MDCT)频谱嫡修正为隐含同步码的压缩域水印,实现了基于音频内容的自同步。算法结合MP3编解码原理对解压后的音频数据分块实施重复嵌入,并根据心理声学模型的掩蔽效应选取合适的嵌入位置,通过处理低频DWT系数完成嵌入。将非压缩域音频信号重新压缩为含有水印信息的MP3码流。 在解码过程中通过频谱墒关系序列定位水印提取位置,实现了水印的盲提取。仿真实验结果表明,算法在保证水印不可感知性的情况下,对抵抗去同步攻击以及Stirmark软件的常见攻击具有良好的鲁棒性。     

Highly Robust, Secure, and Perceptual-Quality Echo Hiding Scheme

Audio watermarking using echo hiding has fairly good perceptual quality. However, security and the tradeoff between robustness and imperceptibility are still relevant issues. This paper presents the echo hiding scheme in which the analysis-by-synthesis approach, interlaced kernels, and frequency hopping are adopted to achieve high robustness, security, and perceptual quality. The amplitudes of the embedded echoes are adequately adapted during the embedding process by considering not only the characteristics of the host signals, but also cases in which the watermarked audio signals have suffered various attacks. Additionally, the interlaced kernels are introduced such that the echo positions of the interlaced kernels for embedding "zero" and "one" are interchanged alternately to minimize the influence of host signals and various attacks on the watermarked data. Frequency hopping is employed to increase the robustness and security of the proposed echo hiding scheme in which each audio segment for watermarking is established by combining the fractions selected from all frequency bands based on a pseudonoise sequence as a secret key. Experimental results indicate that the proposed analysis-by-synthesis echo hiding scheme is superior to the conventional schemes in terms of robustness, security, and perceptual quality.     

A learning-based audio watermarking scheme using kernel Fisher discriminant analysis

A novel learning-based audio watermarking scheme using kernel Fisher discriminant analysis (KFDA) is proposed in this paper. Two techniques, down-sampling technique and energy relationship modulation technique, are developed in order to guarantee good fidelity of the watermarked audio signal. At the same time, local energy relationship between audio sub-frames is hid in the watermarked audio signal with watermark embedding. Moreover, a learning-based watermark detector using the KFDA is exploited and it extracts the watermark by learning the local energy relationship hid in the watermarked audio signal. Due to powerful non-linear learning ability and good generalization ability of the KFDA, the learning-based watermark detector can exhibit high robustness against common audio signal processing or attacks compared with other audio watermarking methods. In addition, it also has simple implementation and lower computation complexity.     

Blind audio watermarking algorithm based on DCT,linear regression and standard deviation

This paper proposes a blind audio watermarking algorithm to embed data and extract them by changing the Discrete Cosine Transform (DCT) coefficients. The key idea is to divide the selected frequency band of DCT into short frames and change the samples of each frame based on the watermark bits that are embedded in. The proposed idea uses linear regression and standard deviation to extract watermark bits. The experimental results show that the method has a high capacity about 3000 bps data payload, without significant perceptual distortion. Moreover, this idea provides robustness against common signal processing attacks such as Additive White Gaussian Noise, Resampling, Re-quantizing and Echo.     

基于DWT和DCT的自适应双重音频水印

针对数字音频版权保护和内容认证的问题, 提出了一种用于版权保护和内容认证的自适应双重音频水印算法。算法对每段原始音频信号进行离散小波变换和离散余弦变换, 分别提取混合变换域的低频系数和中低频系数作为水印的构造和嵌入域, 利用音频载体的统计特性自适应地构造零水印和嵌入半脆弱水印, 实现音频版权保护和内容认证。实验结果表明, 该算法的不可感知性很好, 在抵抗多种攻击时具有良好的鲁棒性, 并且能够对恶意窜改进行定位。     

基于心理声学模型的盲音频数字水印改进型算法

以往基于离散小波变换的音频数字水印算法鲁棒性不强,无法对数字音频信号的版权进行真正地保护,因此改进了算法,利用心理声学模型,控制水印信号的嵌入,通过计算音频信号的掩蔽阀值,在保证水印嵌入不可察觉的前提下,增大水印的嵌入强度。仿真实验证明,该算法具有较强的鲁棒性和不可感知性,能有效抵御各种常见攻击,并且能实现盲检测。     

基于小波和倒谱域的数字音频水印算法

给出一种基于小波和倒谱域的强鲁棒数字音频水印算法。该算法利用人耳听觉模型和频率掩蔽效应,选择出音频小波变换后对人耳听觉不敏感的低频系数,对其进行分帧并作倒谱变换。再利用倒谱域能量集中在零点附近的特性,将一段伪随机序列嵌入在每帧相对稳定的倒谱系数中,从而实现水印的嵌入。采用相关检测的方法,根据相关值的极性来提取水印信息。实验表明,嵌入水印后的音频信号不仅具有良好的不可感知性,而且对诸如加噪、低通滤波、重采样、重量化、回声、MP3压缩和去同步等攻击具有很强的鲁棒性。     

High payload multi-channel dual audio watermarking algorithm based on discrete wavelet transform and singular value decomposition

Digital watermarking technology is concerned with solving the problem of copyright protection, data authentication, content identification, distribution, and duplication of the digital media due to the great developments in computers and Internet technology. Recently, protection of digital audio signals has attracted the attention of researchers. This paper proposes a new audio watermarking scheme based on discrete wavelet transform (DWT), singular value decomposition (SVD), and quantization index modulation (QIM) with a synchronization code embedded with two encrypted watermark images or logos inserted into a stereo audio signal. In this algorithm, the original audio signal is split into blocks, and each block is decomposed with a two-level DWT, and then the approximate low-frequency sub-band coefficients are decomposed by SVD transform to obtain a diagonal matrix. The prepared watermarking and synchronization code bit stream is embedded into the diagonal matrix using QIM. After that, we perform inverse singular value decomposition (ISVD) and inverse discrete wavelet transform (IDWT) to obtain the watermarked audio signal. The watermark can be blindly extracted without knowledge of the original audio signal. Experimental results show that the transparency and imperceptibility of the proposed algorithm is satisfied, and that robustness is strong against popular audio signal processing attacks. High watermarking payload is achieved through the proposed scheme.     

基于DWT-DCT和Zernike矩的灰度级鲁棒性水印算法

鲁棒性是数字水印极为重要的指标.目前大多数文献中的鲁棒性水印方案对常规信号处理攻击均具有良好的鲁棒性,但抗几何攻击的鲁棒性相对较弱.提出了一种新的灰度级鲁棒性水印算法,对常规信号处理攻击和几何攻击均具有良好的鲁棒性.水印算法的鲁棒性由以下3方面获得:1)选择载体图像的内切圆盘作为Zernike矩的计算域,选择内切圆盘的内接正方形作为水印的嵌入区域.2)在载体图像嵌入区域的层叠DWT-DCT域嵌入水印,获得对常规信号处理攻击的强鲁棒性.3)保存原始含水印图像的2个Zernike矩作为校正几何攻击的参数,获得抗几何攻击能力.实验结果表明,该水印算法嵌入容量大,不仅对大角度旋转和大尺度缩放等几何攻击具有很好的鲁棒性,而且可以有效地抵抗有损压缩和常规信号处理攻击.     

基于对象传播神经网络的抗TSM攻击音频水印算法*

提出了一种基于对象传播神经网络的抗TSM攻击音频水印算法。利用CPN自学习和自适应的特征,通过自适应改变段长的分段算法,选用具有较强稳定性的小波低频系数方差作为输入向量训练CPN,建立音频特征与水印信号的对应关系,以达到嵌入水印的目的。实验结果表明,该算法对常规音频信号处理和TSM等同步攻击具有很强的鲁棒性。     

Variable-dimensional vector modulation for perceptual-based DWT blind audio watermarking with adjustable payload capacity

A variable-dimensional vector modulation (VDVM) scheme is introduced to maximize the efficiency of the norm-space DWT-based blind audio watermarking technique. This flexible scheme allows the watermarking algorithm to reach a balance between robustness and capacity, while the imperceptivity is always ensured. The imperfection of applying quantization index modulation in the open-loop case has been rectified. The effectiveness of the proposed scheme is proven using the perceptual evaluation of audio quality (PEAQ) and bit error rates of recovered watermarks under various signal processing attacks. Experimental results show that the proposed VDVM scheme is comparable to other recently developed methods in robustness and imperceptivity even at a capacity as high as 301.46 bps. Such a capacity can be further doubled by halving the dimension of the involved DWT vector, while the robustness is still maintained at a satisfactory level.     

RNS在彩色图像水印中的应用

图像水印技术中,如何平衡鲁棒性和不可见性是技术的难点.余数系统(Residue Number System,RNS)基于中国剩余定理(Chinese Remainder System,CRT),多用于数字信号处理等领域.论文先利用Arnold置乱水印图像,再利用RNS的算法思想将水印图像分解为三通道,分别嵌入到载体图像...     

抗几何攻击的量化鲁棒视频水印技术研究

能有效抵抗信号处理又能抵抗几何攻击是当今数字水印研究的热点和难点之一,提出一种能够抵抗信号处理、旋转、缩放和平移的鲁棒视频水印.嵌入方案中,提出几何不变量——基于圆区域内的统计特征不变性;再依据离散余弦变换域(DCT)系数特性,自适应地在DCT域量化嵌入有意义的水印.提取方案中,利用同步信息定位,若发生几何形变则先矫正形变,然后在DCT域中盲提取水印.结果表明,该方案具有较好的透明性,同时具有较强的抗几何形变能力,对MPEG压缩和去帧等攻击具有很强的鲁棒性.     

An efficient singular value decomposition algorithm for digital audio watermarking

The singular value decomposition (SVD) mathematical technique is utilized, in this paper, for audio watermarking in time and transform domains. Firstly, the audio signal in time or an appropriate transform domain is transformed to a 2-D format. The SVD algorithm is applied on this 2-D matrix, and an image watermark is added to the matrix of singular values (SVs) with a small weight, to guarantee the possible extraction of the watermark without introducing harmful distortions to the audio signal. The transformation of the audio signal between the 1-D and 2-D formats is performed in the well-known lexicographic ordering method used in image processing. A comparison study is presented in the paper between the time and transform domains as possible hosting media for watermark embedding. Experimental results are in favor of watermark embedding in the time domain if the distortion level in the audio signal is to be kept as low as possible with a high detection probability. The proposed algorithm is utilized also for embedding chaotic encrypted watermarks to increase the level of security. Experimental results show that watermarks embedded with the proposed algorithm can survive several attacks. A segment-by-segment implementation of the proposed SVD audio watermarking algorithm is also presented to enhance the detectability of the watermark in the presence of severe attacks.     

基于听觉掩蔽模型和量化的音频水印算法

提出一种基于听觉掩蔽模型的音频数字水印算法,根据掩蔽阚值量化音频经DCT变换后的低频系数来嵌入水印。实验结果证明所嵌入的水印具有很好的不可感知性,对加白噪声、低通滤波和重采样等各种攻击具有良好的鲁棒性。