自适应小波域数字音频水印嵌入算法研究

以整型提升小波变换、人类听觉掩蔽特性、数字音频局部邻域特性为基础，提出了一种自适应小波域数字音频水印嵌入算法，该算法具有以下特点：（1）结合人类听觉系统的掩蔽特性，实现了水印嵌入位置的自适应确定；（2）引入了高效的整型提升小波变换；（3）利用数字音频的局部邻域特性，实现了数字水印嵌入深度的智能调节；（4）数字水印信息的提取不需要原始音频信号．对比实验表明：该自适应数字音频水印算法不仅具有较好的透明性，而且对诸如叠加噪声、有损压缩、低通滤波、重新采样、重新量化等攻击均具有较好的鲁棒性（特别是叠加噪声与低通滤波）。     

用于MP3作品版权保护的数字水印新算法

以MP3压缩攻击特点与听觉掩蔽特性为基础，提出了一种可用于MP3音乐作品版权保护的混合域数字音频盲水印算法．首先，结合MP3压缩等攻击特点，对原始数字音频进行自适应的分段处理；再对每个音频数据段进行DWT和DCT；最后，结合听觉掩蔽特性与MP3压缩攻击特点，自适应确定量化步长，并将水印信号嵌入到音频数据段的低频分量中．仿真实验表明，所提出的算法不仅具有较好的透明性，而且对诸如重新采样、重新量化、叠加噪声、低通滤波等攻击均具有较好的鲁棒性．特别地，该算法对于最为普通的MP3压缩攻击具有极强的抵抗能力（尤其是高压缩比下）．     

一种新的混合域自适应数字音频水印算法

以MP3压缩等攻击特点厦局部音频相关特性为基础，提出了一种新的混合城数字音频盲水印算法．首先，结合MP3压缩等攻击特点，对原始数字音频进行自适应的分段处理；再对每个音频数据段进行DWT和DCT；最后，结合局部音频特性与听觉掩蔽特性，自适应确定量化步长．并将水印信号嵌入到音频数据段的低频分量中．仿真实验表明，本文算法不仅具有较好的透明性，而且对诸如重新采样、重新量化、叠加噪声、低通滤波等攻击均具有较好的鲁棒性．特剐地，该算法对于最为普通的MP3压缩攻击具有极强的抵抗能力．     

一种健壮的数字音频水印时域算法

提出了一种健壮的数字音频水印时域算法。把音频信号划分为若干个包含相同采样点的段,每一段划分为若干个包含相同采样点的节,对每段前二节的能量进行比较,结合水印信号及HAS(人类听觉系统,Human Auditory System)的掩蔽特性,采取不改变或缩小音频信号能量的方法,在数字音频中嵌入水印。实验证明,该算法听觉相似性好,健壮性强,可盲水印检测。     

基于人工神经网络的数字音频水印算法

提出了一种新的基于神经网络训练学习的数字音频水印算法 ,采用本算法在一段数字音频数据中隐藏了一幅不可感知的二值图像 .通过后向传播算法的神经网络训练出模板信号与嵌入了水印信号的音频之间的关系特征 ,由于神经网络具有学习和自适应的特性 ,通过训练后的神经网络几乎能够完全恢复嵌入到音频中的水印数据 .通过仿真实验结果表明该算法具有较好的鲁棒性和抵抗常用的信号处理方法的处理的能力 ,特别是在水印检测时不需要原始的音频信号 .     

A pseudo-Zernike moment based audio watermarking scheme robust against desynchronization attacks

Desynchronization attack is known as one of the most difficult attacks to resist, for it can desynchronize the location of the watermark and hence causes incorrect watermark detection. It is a challenging work to design a robust audio watermarking scheme against desynchronization attacks. Based on pseudo-Zernike moment and synchronization code, we propose a new digital audio watermarking algorithm with good auditory quality and reasonable resistance toward desynchronization attacks in this paper. Firstly, the origin digital audio is segmented and then each segment is cut into two parts. Secondly, with the spatial watermarking technique, synchronization code is embedded into the statistics average value of audio samples in the first part. And then, map 1D digital audio signal in the second part into 2D form, and calculate its pseudo-Zernike moments. Finally, the watermark bit is embedded into the average value of modulus of the low-order pseudo-Zernike moments. Meanwhile combining the two adjacent synchronization code searching technology, the algorithm can extract the watermark without the help from the origin digital audio signal. Simulation results show that the proposed watermarking scheme is not only inaudible and robust against common signals processing such as MP3 compression, noise addition, resampling, re-quantization, etc., but also robust against the desynchronization attacks such as random cropping, amplitude variation, pitch shifting, jittering, etc.     

DCT域音频水印算法的嵌入位置选择策略

本文在DCT最大误差模型研究的基础上提出了一种新的音频水印嵌入位置选择策略。建立了水印嵌入位置和嵌入水印后的音频文件的听觉感知性之阿的关系,根据音频水印的不可听性的要求选择最优的嵌入位置,然后选择不同的水印强度调整鲁棒性,从而最大程度地保持音频水印的不可听性和鲁棒性,为解决音频水印嵌入过程中不可听性和鲁棒性之间的矛盾提供了一种策略。     

Audio watermarking scheme with dynamic adjustment in mute period

Watermark is some imperceptible information embedded into the work for later verification and thus it can be used to prove the originality or to protect the work from being illegally copied or modified. Kaabneh and Youssef (2001) proposed a muteness-based watermarking method for audio file. Their method can successfully embed watermarking information into audio file such that the human ears cannot distinguish the covered work from the original one. To improve the efficiency, we proposed a watermarking method for audio files in this paper. By adjusting the length of mute period dynamically, the proposed method can achieve the goal of watermark embedding with little variation of the original work. Experiment has shown that our method has the advantages of efficiency and fidelity as compared with theirs. Furthermore, it does not require the original audio file to derive the embedded watermark.     

Robust multi bit and high quality audio watermarking using pseudo-random sequences

A robust multi bit and high quality audio watermarking technique in time domain is proposed in this paper. Watermarking is a technique used to label digital media by hiding copyright or other information into the underlying data. The watermark must be imperceptible and undetectable by the user and should be robust to various types of distortion. To enhance the robustness and taper-resistance of the embedded watermark, in this paper a multi bit technique is employed. Instead of embedding one bit into an audio frame, multiple bits can be embedded into each audio sub-frame. For attackers, since they do not know the parameters, this significantly reduces the possibility of unauthorized bit detection and removal of watermark. In real-time watermarking applications, robustness is not the only factor that plays an important role. The other factor that plays a very an important role is computational complexity. In general, audio file is transmitted in compressed form. Real-time watermark embedding must take into account this compressed form, because first decompressing the data, adding a watermark and then recompressing the data is computationally too demanding. In this paper, we propose robust and low complexity audio watermarking algorithm. To evaluate the performance of the proposed audio watermarking algorithm, subjective and objective quality tests including bit error rate (BER) and signal-to-noise ratio (SNR) were conducted. Compared to traditional one bit embedding algorithm, the proposed algorithm gives highly recovery rate after attack by commonly used audio data manipulations, such as low pass filtering, requantization, resampling, and MP3 compression.     

Audio watermarking scheme based on embedding strategy in low frequency components with a binary image

With the recent development of information technology and computer network, digital format of data has become more and more popular. However, a major problem faced by digital data providers and owners is protecting data from unauthorized copying and distribution. As a solution to the problem, digital watermark technology is now attracting attention as new method of protection against said unauthorized copying and distribution. The aim of the digital audio watermarking is to take prespecified data that carries certain information and hide it within the audio stream such that it is not audible to the human ear (i.e., transparent) but at the same time renders the file more resistant to removal (i.e., robust). In this paper, we propose a new method for embedding digital watermarks into audio signals in low frequency components, which method mitigates these and other related shortcomings. The proposed method uses the wavelet transform constructed by lifting-based wavelet transform (LBWT) in order to provide a fast implementation between watermark embedding and extraction parts. In the first stage of the proposed method, the original audio host signal is converted to a wavelet domain using LBWT. The signal is thus decomposed into low and high frequency components. Approximation coefficients correspond to low frequency components of the signal. Next, the watermark generated by pseudorandom numbers is embedded into wavelet approximation coefficients of the segmented host audio signal depending on the binary value of the binary image. The reason for embedding the watermark in the low frequency components is that these components' energy is greater than that of high frequency components in such a way that the watermark is inaudible; therefore, it should not alter the audible content and should not be easy to remove. The proposed method uses a binary image to decide whether or not the watermark generated by pseudorandom numbers is embedded in the audio host signal. To evaluate the performance of the proposed audio watermarking method, subjective and objective quality tests including bit error rate (BER) and signal-to-noise ratio (SNR) are conducted. The tests' results show that the proposed method yields a high recovery rate after attacks by commonly used audio data manipulations such as low-pass filtering, requantization, resampling and MP3 compression.     

基于支持向量机(SVM)的数字音频水印

提出了一种新的基于支持向量机（support vector machine,SVM）的数字音频水印算法．主要思想是在宿主音频中嵌入一段模板信息,定义模板信息与宿主音频之间的一种对应关系．将水印的检测问题转化为一个可用SVM处理的二分类问题,利用SVM对先验知识（对应关系）的学习,以达到对未知数字音频水印的正确分类检测．仿真实验结果表明,该数字音频水印具有较强的健壮性和不可感知性,在受到MP3压缩、低通滤波、重采样／量化、噪声干扰等常用信号处理方法的处理后,能正确检测出水印,同时在水印检测时不需要原始音频,实现了水印的盲检测．     

Localized audio watermarking technique robust against time-scale modification

Synchronization attacks like random cropping and time-scale modification are very challenging problems to audio watermarking techniques. To combat these attacks, a novel content-dependent localized robust audio watermarking scheme is proposed. The basic idea is to first select steady high-energy local regions that represent music edges like note attacks, transitions or drum sounds by using different methods, then embed the watermark in these regions. Such regions are of great importance to the understanding of music and will not be changed much for maintaining high auditory quality. In this way, the embedded watermark has the potential to escape all kinds of distortions. Experimental results show strong robustness against common audio signal processing, time-domain synchronization attacks, and most distortions introduced in Stirmark for Audio.     

一种可抵抗MP3压缩的音频水印算法

提出了一种稳健的自适应混合域数字音频水印算法，该算法具有以下特点:(1)通过采纳更为稳健的同步信号及其全新嵌入策略，提高了音频水印的抗攻击能力；(2)充分利用DWT的多分辨率特性和DCT的能量压缩特性，改善了数字水印的隐藏效果；(3)结合听觉掩蔽特性自适应确定量化步长，提高了数字水印的不可感知性；(4)以保证不可感知性和稳健性的良好平衡为前提，实现了数字水印的盲检测．仿真实验表明，所提出的算法不仅具有较好的不可感知性，而且对诸如重新采样、重新量化、叠加噪声、低通滤波、随机剪切等攻击均具有较好的稳健性．特别地，该算法对于最为普通的MP3压缩攻击具有极强的抵抗能力(尤其是高压缩比下).     

一种基于 DWT 的音频水印算法

基于人耳听觉特性和小波变换的时频特性,提出了一种水印嵌入与检测算法。通过提取音频信号幅度的最大值进行小波变换,再在小波变换的重要系数中嵌入水印。仿真实验证明:该算法隐藏水印具有较好的不可感知性和较强的稳健性。     

基于内容的自适应小波域数字音频水印算法研究

以整型提升小波变换、静态图像压缩编码、人类听觉系统（HAS）为基础，提出了一种将灰度图像（即二维数字水印）嵌入到数字音频信号的新水印算法．该算法具有以下特点：（1）应用静态图像压缩编码技术，实现了以灰度图像作为水印信号的数字音频水印算法；（2）充分利用人类听觉系统（HAS），实现了二维数字水印的自适应嵌入，增强了算法的透明性和鲁棒性，（3）二维数字水印的提取不需要原始音频信号．仿真实验表明：该自适应数字音频水印算法不仅具有较好的透明性，而且对诸如叠加噪声、有损压缩、低通滤波、重新采样、重新量化等攻击均具有较好的鲁棒性．     

基于MCLT变换的音频数字水印技术

在网络与数字信息给人们带来方便的同时，也给人们带来了隐患：敏感信息可能轻易地被窃取、篡改、非法复制和传播等．信息的安全与保密显得越来越重要，信息安全已成为人们关心的焦点，也是当今信息领域的研究热点之一．提出了基于MCLT变换的谱弯折音频水印算法，利用谱弯折技术，通过调整MCLT变换的角频率，可将视觉可辨的二值图像嵌人音频之中，实现水印在整个频域嵌入，算法的最大优点是嵌入量较大．经实验验证，认为谱弯折方法对MP3压缩、重采样等的攻击相当脆弱，不具备鲁棒性，属半易碎型音频水印．     

Robust audio watermarking in the time domain

The audio watermarking method proposed in this paper offers copyright protection to an audio signal by time domain processing. The strength of audio signal modifications is limited by the necessity to produce an output signal that is perceptually similar to the original one. The watermarking method presented here does not require the use of the original signal for watermark detection. The watermark signal is generated using a key, i.e., a single number known only to the copyright owner. Watermark embedding depends on the audio signal amplitude and frequency in a way that minimizes the audibility of the watermark signal. The embedded watermark is robust to common audio signal manipulations like MPEG audio coding, cropping, time shifting, filtering, resampling, and requantization     

一种基于倒谱变换的自适应音频水印算法*

结合人类听觉系统,提出了一种基于倒谱变换的自适应音频水印算法,充分利用复倒谱变换的性质,将原始音频信号分成若干帧,每帧实施复倒谱变换后,在对应位置按照一定的方法嵌入水印信号。水印的提取不需要原始音频信号,是一种盲水印算法。实验结果表明,嵌入后的水印不仅具有很好的不可感知性,而且对添加噪声、重新采样、低通滤波和重新量化等攻击也具有很好的鲁棒性。     

A New Adaptive Digital Audio Watermarking Based on Support Vector Regression

On the basis of support vector regression (SVR), a new adaptive blind digital audio watermarking algorithm is proposed. This algorithm embeds the template information and watermark signal into the original audio by adaptive quantization according to the local audio correlation and human auditory masking. The procedure of watermark extraction is as follows. First, the corresponding features of template and watermark are extracted from the watermarked audio. Then, the corresponding feature of template is selected as training sample to train SVR and an SVR model is returned. Finally, the actual outputs are predicted according to the corresponding feature of watermark, and the digital watermark is recovered from the watermarked audio by using the well-trained SVR. Experimental results show that our audio watermarking scheme is not only inaudible, but also robust against various common signal processing (such as noise adding, resampling, requantization, and MP3 compression), and also has high practicability. In addition, the algorithm can extract the watermark without the help of the original digital audio signal, and the performance of it is better than other SVM audio watermarking schemes.     

基于音频特征的多小波域水印算法

基于对音频特征的分析,提出了一种多小波域的水印算法.结合人类听觉系统的时频掩蔽特性,该算法分析音频帧的过零率及时域能量,确定用于嵌入水印的帧.利用音频的分抽样特征和多小波变换在信号处理中的优势,将每一个音频帧进行分抽样为两个子音频帧并分别将其变换到多小波域.利用两个子音频帧在多小波域的能量来估计所嵌入水印的容量,并根据它们的能量大小关系完成水印的嵌入.水印的提取过程转为一个使用支持向量机进行处理的二分类问题.实验结果验证了所提出的水印算法能根椐音频自身的特点寻找到适合用于嵌入水印的音频帧,且能动态调整水印的嵌入强度,在保证听觉质量的同时提高了水印的鲁棒性.