数字音频水印技术的研究和实现
|
摘要
随着互联网和计算机技术的普及和飞速发展,数字多媒体产品得到了广泛应用。如何在网络环境下实施数字产品的版权保护、合法权益和信息安全,成为数字通信中亟待解决的问题。数字水印技术的发展提供了解决这一问题的新思路。随着以MP3为代表的音乐产品在网络上广泛传播,数字音频水印技术逐渐成为国内外学术界研究的热点。
本论文重点研究数字音频水印技术,并在此基础之上,给出水印图像恢复的新思路。给出了两种基于独立分量分析(Independent Component Analysis,ICA)的数字音频水印方法和一种基于码本映射的分块离散Hopfield网络的水印图像恢复方法。首先,阐述了课题提出的意义和研究背景。其次,介绍了本论文中用到的基本理论知识。接着,给出了两种基于ICA的小波域数字音频水印方法。第一种方法针对数字水印算法对抗时间轴同步攻击能力较弱,以及版权保护和音频信号感兴趣区域(Region of Interest,ROI)内容保护的问题,给出了一种基于ICA的自同步小波域多目的音频水印方法,实现了对音频信号重要音频段和版权标识保护的双重目的。第二种方法针对多著作权版权保护、音频重要音频段内容保护和篡改定位的问题,给出了一种基于ICA的小波域多重和多目的音频水印方法,该方法把音频信号的ROI和两个图像标识嵌入到宿主信号中,实现了水印技术的多重性和多目的性这两个重要特性,并且只需嵌入鲁棒水印而不需要嵌入脆弱水印即可实现篡改定位的功能。最后,针对水印领域中经常遇到的版权标识遭受恶意攻击而无法有力保护版权的问题,给出了一种基于码本映射的分块Hopfield网络的水印图像恢复方法,该方法通过码本映射的方式解决了Hopfield网络权矩阵占用空间大的问题;采用对图像进行分块和降低相关性的方法,提高了网络对模糊图像的恢复性能。
实验结果表明,给出的两种水印方法均满足音频水印技术对透明性、鲁棒性和安全性的要求,可以用于数字音频产品的版权保护、内容保护或篡改区域定位;给出的针对模糊水印图像的恢复方法,改善了传统水印系统的性能,进一步达到了版权保护的目的。
As the prevalence and of rapid development computers and Internet, digital multimedia product has been applied widely. How to carry out copyright protection, copyright protection and information security on the Internet has become one of the urgent problems to be solved in digital communication. The development of digital watermark technique becomes a novel way to solve this problem. As music products like MP3 are widely spread on the Internet, digital audio watermarking technique becomes an internationally hot topic at present.
In this paper, the main task focuses on digital audio watermarking scheme. And then, watermarking image restoration scheme is also provided, which is based on the audio watermarking scheme. Two kinds of digital audio watermarking schemes based on Independent Component Analysis (ICA) and one kind of watermarking image restoration scheme based on codebook mapping and blocked discrete Hopfield network are provided in this paper. Firstly, the meaning of the task and the research background are introduced. Secondly, basic background knowledge related is introduced. After that, two kinds of digital audio watermarking schemes based on ICA in wavelet transformed domain are proposed. Aiming at the problems that most existing digital audio watermarking schemes can weakly resist time-scale attack, and copyright protection and Region of Interest (ROI) of audio signal protection, a multipurpose digital audio watermarking scheme in the wavelet transformed domain based on ICA and synchronization is proposed, which realizes two purposes: ROI important audio segment protection and single copyright protection. Aiming at multiple copyrights protection, important segment audio content protection and tampered areas localization, a multiple and multipurpose audio watermarking scheme in the wavelet transformed domain based on ICA is proposed, which embeds one ROI audio signal and two image signals into the host signal. Owning two important characters: multiple and multipurpose, this scheme achieves the purpose of tampering localization only embedding robust watermarking signals, but not fragile watermarking signals. At last, aiming at the effective copyright protection even when the copyright symbols have undergone serious attacks, a watermarking image restoration scheme based on codebook mapping and blocked discrete Hopfield network is proposed, which solves the large space assuming problem of weight matrix of Hopfield network by codebook mapping, and enhances the network restoration performance by blocking scheme and reducing correlation of watermarking images.
Experimental results show that both of the two audio watermarking schemes can satisfy the requirements of transparency, robustness and security, and can be applied in copyright protection, content protection or tampered areas localization; the blurred watermarking image restoration scheme can improve the performance of the traditional watermarking system and achieve the purpose of the copyright protection more effectively.
本论文重点研究数字音频水印技术,并在此基础之上,给出水印图像恢复的新思路。给出了两种基于独立分量分析(Independent Component Analysis,ICA)的数字音频水印方法和一种基于码本映射的分块离散Hopfield网络的水印图像恢复方法。首先,阐述了课题提出的意义和研究背景。其次,介绍了本论文中用到的基本理论知识。接着,给出了两种基于ICA的小波域数字音频水印方法。第一种方法针对数字水印算法对抗时间轴同步攻击能力较弱,以及版权保护和音频信号感兴趣区域(Region of Interest,ROI)内容保护的问题,给出了一种基于ICA的自同步小波域多目的音频水印方法,实现了对音频信号重要音频段和版权标识保护的双重目的。第二种方法针对多著作权版权保护、音频重要音频段内容保护和篡改定位的问题,给出了一种基于ICA的小波域多重和多目的音频水印方法,该方法把音频信号的ROI和两个图像标识嵌入到宿主信号中,实现了水印技术的多重性和多目的性这两个重要特性,并且只需嵌入鲁棒水印而不需要嵌入脆弱水印即可实现篡改定位的功能。最后,针对水印领域中经常遇到的版权标识遭受恶意攻击而无法有力保护版权的问题,给出了一种基于码本映射的分块Hopfield网络的水印图像恢复方法,该方法通过码本映射的方式解决了Hopfield网络权矩阵占用空间大的问题;采用对图像进行分块和降低相关性的方法,提高了网络对模糊图像的恢复性能。
实验结果表明,给出的两种水印方法均满足音频水印技术对透明性、鲁棒性和安全性的要求,可以用于数字音频产品的版权保护、内容保护或篡改区域定位;给出的针对模糊水印图像的恢复方法,改善了传统水印系统的性能,进一步达到了版权保护的目的。
As the prevalence and of rapid development computers and Internet, digital multimedia product has been applied widely. How to carry out copyright protection, copyright protection and information security on the Internet has become one of the urgent problems to be solved in digital communication. The development of digital watermark technique becomes a novel way to solve this problem. As music products like MP3 are widely spread on the Internet, digital audio watermarking technique becomes an internationally hot topic at present.
In this paper, the main task focuses on digital audio watermarking scheme. And then, watermarking image restoration scheme is also provided, which is based on the audio watermarking scheme. Two kinds of digital audio watermarking schemes based on Independent Component Analysis (ICA) and one kind of watermarking image restoration scheme based on codebook mapping and blocked discrete Hopfield network are provided in this paper. Firstly, the meaning of the task and the research background are introduced. Secondly, basic background knowledge related is introduced. After that, two kinds of digital audio watermarking schemes based on ICA in wavelet transformed domain are proposed. Aiming at the problems that most existing digital audio watermarking schemes can weakly resist time-scale attack, and copyright protection and Region of Interest (ROI) of audio signal protection, a multipurpose digital audio watermarking scheme in the wavelet transformed domain based on ICA and synchronization is proposed, which realizes two purposes: ROI important audio segment protection and single copyright protection. Aiming at multiple copyrights protection, important segment audio content protection and tampered areas localization, a multiple and multipurpose audio watermarking scheme in the wavelet transformed domain based on ICA is proposed, which embeds one ROI audio signal and two image signals into the host signal. Owning two important characters: multiple and multipurpose, this scheme achieves the purpose of tampering localization only embedding robust watermarking signals, but not fragile watermarking signals. At last, aiming at the effective copyright protection even when the copyright symbols have undergone serious attacks, a watermarking image restoration scheme based on codebook mapping and blocked discrete Hopfield network is proposed, which solves the large space assuming problem of weight matrix of Hopfield network by codebook mapping, and enhances the network restoration performance by blocking scheme and reducing correlation of watermarking images.
Experimental results show that both of the two audio watermarking schemes can satisfy the requirements of transparency, robustness and security, and can be applied in copyright protection, content protection or tampered areas localization; the blurred watermarking image restoration scheme can improve the performance of the traditional watermarking system and achieve the purpose of the copyright protection more effectively.
引文
[1]Wang H Q,Nishimura R,Suzuki Yet al.Fuzzy self-adaptive digital audio watermarking based on time-spread echo hiding.Applied Acoustics,2008,69(10):868-874.
[2]Kumar S K,Sreenivas T.Increased watermark-to-host correlation of uniform random phase watermarks in audio signals.Signal Processing,2007,87(1):61-67.
[3]施化吉,唐慧,郑洪源等.一种自适应的同步音频水印算法.华南理工大学学报,2008,36(9):59-63.
[4]Chen W Y,Chen C H.A robust watermarking scheme using phase shift keying with the combination of amplitude boost and low amplitude block selection.Pattern Recognition,2005,38(4):587-598.
[5]马晓红,孙长富.基于盲源分离的小波域多重音频水印方法.电子与信息学报,2008,30(10):2307-2310.
[6]Wu S Q,Huang J W,Huang D R.Efficiently self-synchronized audio watermarking for assured audio data transmission.IEEE Transactions on Broadcasting,2005,51(1):69-76.
[7]Wang X Y,Zhao H.A novel synchronization invariant audio watermarking scheme based on DWT and DCT.IEEE Transactions on Signal Processing,2006,54(12):4835-4840.
[8]杨义先,钮心忻.数字水印理论与技术.北京:高等教育出版社,2006.
[9]袁一群,李伟,陆佩忠.一种新的音频内容认证算法.计算机工程,2007,33(10):147-149.
[10]赵红,沈东升,朱元辉.一种抗裁剪的半脆弱音频水印算法.自动化学报,2008,34(6):647-651.
[11]全笑梅,张鸿宾.用于篡改检测及认证的脆弱音频水印算法.电子与信息学报,2005,27(8):1187-1192
[12]Choi Y H,Choi T S.Multipurpose logo embedding method for copyright protection and authentication.IEEE International Conference on Consumer Electronics,2006 Digest of Technical Papers,Las Vegas,USA,2006:241-242.
[13]Wang R D,Xu D W,Li Q.Multiple audio watermarks based on lifting wavelet transform.International conference on Machine Learning and Cybernetics,Guangzhou,China,2005,4:1959-1964.
[14]Chen N,Zhu J.A multipurpose audio watermarking scheme for copyright protection and content authentication.IEEE International Conference on Multimedia and Expo,Hannover,Germany,2008:221-224.
[15]Fan M Q,Wang H X.A Novel Multipurpose Watermarking Scheme for Copyright Protection and Content Authentication.Second Workshop on Digital Media and its Application in Museum & Heritage,Chongqing,China,2007:19-24.
[16]Ma X H,Ding X Y,Wang C et al.A Blind Source Separation Based Multi-bit Digital Audio Watermarking Scheme.International Symposium on Neural Networks,Chengdu,China,2006.Berlin/Heidelberg:Springer,2006,3973:306-311.
[17]王向阳,祁薇.用于版权保护与内容认证的半脆弱音频水印算法.自动化学报,2007,33(9):936-940.
[18]赵友军,邸兰振.感兴趣区域的自适应可见水印技术.计算机工程,2007,33(9):180-181.
[19]鲁继文,张二虎.一种基于混沌和独立成分分析的自适应多重数字水印算法.计算机应用,2005,25(12):2736-2738.
[20]陈金儿,王让定,王晓丽.数字音频双重水印算法.宁波大学学报(理工版),2006,19(1):54-58.
[21]吴艺杰,杨晓云,魏立线等.一种新颖的音频双水印算法.计算机工程与应用,2006,42(26):33-35.
[22]Lee J J,Kim W,Lee NY,et al.A new incremental watermarking based on dual-tree complex wavelet transform.The Journal of Supercomputing,2005,33(1):133-140.
[23]Xiang S J,Huang J W,Yang R.Time-Scale Invariant Audio Watermarking Based on the Statistical Features in Time Domain.The 8th Information Hiding Workshop,Old Town Alexandria,USA,2006,4437:93-108.
[24]Wang X Y,Niu P P,Qi W.A new adaptive digital audio watermarking based on support vector machine.Journal of Network andComputer Applications,2008,31(4):735-749.
[25]梁忠杰,数字音频鲁棒水印技术的研究:(硕士学位论文).大连:大连理工大学,2006.
[26]Ercetebi E,Subasl A.Robust multi bit and high quality audio watermarking using pseudo-random sequences.Computers & Electrical Engineering,2005,31(8):525-536.
[27]杨福生.小波变换的工程分析与应用.北京:科学出版社,1999.
[28]施吉林,张宏伟,金光日.计算机科学计算.北京:高等教育出版社,2005.
[29]马晓红.传声器阵列语音增强中关键技术的研究:(博士学位论文).大连:大连理工大学,2006.
[30]Lee J A,Vrins F,Verleysen M.Blind source separation based on endpoint estimation with application to the MLSP 2006 data competition.Neurocomputing,2008,72(1-3):47-56.
[31]Saruwatari H,Kawamura T,Nishikawa T et al.Blind source separation based on a fast-convergence algorithm combining ICA and beamforming.IEEE Transactions on Audio,Speech,and Language Processing,2006,14(2):666-678.
[32]Narozny M,Barret M Dinh-Tuan Pham D T.ICA based algorithms for computing optimal 1-D linear block transforms in variable high-rate source coding.Signal Processing,2008,88(2):268-283.
[33]Pei S C,Zeng Y C.A novel image recovery algorithm for visible watermarked images.IEEE Transactions on Information Forensic and Security,2006,1(4):543-550.
[34]Wang F S,Li H W,Li R.Unified parametric and nonparametric ICA algorithms for hybrid source signals and stability analysis.International Journal of Innovative Computing,Information and Control,2008,4(4):933-942.
[35]Ranganathan R,Mikhael W B.A comparative study of complex gradient and fixed-point ICA algorithms for interference suppression in static and dynamic channels.Signal Processing,2008,88(2):399-406.
[36]Squartini S,Arcangeli A,Piazza F.Stability analysis of natural gradient learning rules in overdetermined ICA.Signal Processing,2008,88(3):761-766.
[37]Ye Y,Zhang Z L,Zeng J Z et al.A fast and adaptive ICA algorithm with its application to fetal electrocardiogram extraction.Applied Mathematics and Computation,2008,205(2):799-806.
[38]Lee I,Kim T,Lee T W.Fast fixed-point independent vector analysis algorithms for convolutive blind source separation.Signal Processing,2007,87(8):1859-1871.
[39]Hyv(a|¨)rinen A,Oja E.A fast fixed-point algorithm for independent component analysis.Neural Computation,1997,9(7):1483-1492.
[40]Hyv(a|¨)rinen A.Fast and robust fixed-point algorithms for independent component analysis.IEEE Transactions on Neural Networks,1999,10(3):626-634.
[41]Shen H,Kleinsteuber M,H(u|¨)per H.Local convergence analysis of fastICA and related algorithms.IEEE Transactions on Neural Networks,2008,19(6):1022-1032.
[42]Douglas S C,Gupta M,Sawada H et al.Spatio-temporal fastICA algorithms for the blind separation of convolutive mixtures.IEEE Transactions on Audio,Speech,and Language Processing,2007,15(5):1511-1520.
[43]谭文,王耀南.混沌系统的模糊神经网络控制理论与方法.北京:科学出版社,2008.
[44]焦李成,杨淑嫒.自适应多尺度神经网络理论与应用.北京:科学出版社,2008.
[45]Hopfield J J.Neural networks and physical systems with emergent collective computational abilities.Proceedings of the National Academy of Sciences,USA,1982,79:2554-2558.
[46]夏定纯,徐涛.计算智能.北京:科学出版社,2008.
[47]张仰森,黄改娟.人工智能教程.北京:高等教育出版社,2008.
[48]雷赟,刘建,严波等.窄带的自同步音频水印算法.计算机学报,2008,31(7):1283-1290.
[49]王虹,孙毅.基于水印序号的抗裁剪音频数字水印算法.武汉理工大学学报,2008,32(3):481-484.
[50]Foo S W,Xue F,Li M Y.A blind audio watermarking scheme using peak point extraction.IEEE International Symposium on Circuit and Systems,Kobe,Japan,2005:4409-4412.
[51]Ma X H,Zhang B,Ding X H.Self-synchronization blind audio watermarking based on feature extraction and subsampling.International Symposium on Neural Networks,Nanjing,China,2007.Berlin/Heidelberg:Springer,2007,4492:40-46.
[52] Wang S S, Tsai S L. Automatic image authentication and recovery using fractal code embedding and image inpainting. Pattern Recognition, 2008, 41(2): 701-712.
[53] Shih F Y, Wu Y T. Robust watermarking and compression for medical images based on genetic algorithms. Information Sciences, 2005, 175(3): 200-216.
[54] Mooney A, Keating J G, Heffernan D M. A detailed study of the generation of optically detectable watermarks using the logistic map. Chaos, Solitons & Fractals, 2006, 30(5):1088-1097.
[55] Xiang F, Qiu S S. Analysis on stability of binary chaotic pseudorandom sequence. IEEE Communications Letters, 2008, 12: 337-339.
[56] Tsuneda A, Mitsuishi S, Inoue T. A study on generation of random bit sequences with post-processing by linear feedback shift registers. International Journal of Innovative Computing, Information and Control, 2008, 4(10): 2631-2638.
[2]Kumar S K,Sreenivas T.Increased watermark-to-host correlation of uniform random phase watermarks in audio signals.Signal Processing,2007,87(1):61-67.
[3]施化吉,唐慧,郑洪源等.一种自适应的同步音频水印算法.华南理工大学学报,2008,36(9):59-63.
[4]Chen W Y,Chen C H.A robust watermarking scheme using phase shift keying with the combination of amplitude boost and low amplitude block selection.Pattern Recognition,2005,38(4):587-598.
[5]马晓红,孙长富.基于盲源分离的小波域多重音频水印方法.电子与信息学报,2008,30(10):2307-2310.
[6]Wu S Q,Huang J W,Huang D R.Efficiently self-synchronized audio watermarking for assured audio data transmission.IEEE Transactions on Broadcasting,2005,51(1):69-76.
[7]Wang X Y,Zhao H.A novel synchronization invariant audio watermarking scheme based on DWT and DCT.IEEE Transactions on Signal Processing,2006,54(12):4835-4840.
[8]杨义先,钮心忻.数字水印理论与技术.北京:高等教育出版社,2006.
[9]袁一群,李伟,陆佩忠.一种新的音频内容认证算法.计算机工程,2007,33(10):147-149.
[10]赵红,沈东升,朱元辉.一种抗裁剪的半脆弱音频水印算法.自动化学报,2008,34(6):647-651.
[11]全笑梅,张鸿宾.用于篡改检测及认证的脆弱音频水印算法.电子与信息学报,2005,27(8):1187-1192
[12]Choi Y H,Choi T S.Multipurpose logo embedding method for copyright protection and authentication.IEEE International Conference on Consumer Electronics,2006 Digest of Technical Papers,Las Vegas,USA,2006:241-242.
[13]Wang R D,Xu D W,Li Q.Multiple audio watermarks based on lifting wavelet transform.International conference on Machine Learning and Cybernetics,Guangzhou,China,2005,4:1959-1964.
[14]Chen N,Zhu J.A multipurpose audio watermarking scheme for copyright protection and content authentication.IEEE International Conference on Multimedia and Expo,Hannover,Germany,2008:221-224.
[15]Fan M Q,Wang H X.A Novel Multipurpose Watermarking Scheme for Copyright Protection and Content Authentication.Second Workshop on Digital Media and its Application in Museum & Heritage,Chongqing,China,2007:19-24.
[16]Ma X H,Ding X Y,Wang C et al.A Blind Source Separation Based Multi-bit Digital Audio Watermarking Scheme.International Symposium on Neural Networks,Chengdu,China,2006.Berlin/Heidelberg:Springer,2006,3973:306-311.
[17]王向阳,祁薇.用于版权保护与内容认证的半脆弱音频水印算法.自动化学报,2007,33(9):936-940.
[18]赵友军,邸兰振.感兴趣区域的自适应可见水印技术.计算机工程,2007,33(9):180-181.
[19]鲁继文,张二虎.一种基于混沌和独立成分分析的自适应多重数字水印算法.计算机应用,2005,25(12):2736-2738.
[20]陈金儿,王让定,王晓丽.数字音频双重水印算法.宁波大学学报(理工版),2006,19(1):54-58.
[21]吴艺杰,杨晓云,魏立线等.一种新颖的音频双水印算法.计算机工程与应用,2006,42(26):33-35.
[22]Lee J J,Kim W,Lee NY,et al.A new incremental watermarking based on dual-tree complex wavelet transform.The Journal of Supercomputing,2005,33(1):133-140.
[23]Xiang S J,Huang J W,Yang R.Time-Scale Invariant Audio Watermarking Based on the Statistical Features in Time Domain.The 8th Information Hiding Workshop,Old Town Alexandria,USA,2006,4437:93-108.
[24]Wang X Y,Niu P P,Qi W.A new adaptive digital audio watermarking based on support vector machine.Journal of Network andComputer Applications,2008,31(4):735-749.
[25]梁忠杰,数字音频鲁棒水印技术的研究:(硕士学位论文).大连:大连理工大学,2006.
[26]Ercetebi E,Subasl A.Robust multi bit and high quality audio watermarking using pseudo-random sequences.Computers & Electrical Engineering,2005,31(8):525-536.
[27]杨福生.小波变换的工程分析与应用.北京:科学出版社,1999.
[28]施吉林,张宏伟,金光日.计算机科学计算.北京:高等教育出版社,2005.
[29]马晓红.传声器阵列语音增强中关键技术的研究:(博士学位论文).大连:大连理工大学,2006.
[30]Lee J A,Vrins F,Verleysen M.Blind source separation based on endpoint estimation with application to the MLSP 2006 data competition.Neurocomputing,2008,72(1-3):47-56.
[31]Saruwatari H,Kawamura T,Nishikawa T et al.Blind source separation based on a fast-convergence algorithm combining ICA and beamforming.IEEE Transactions on Audio,Speech,and Language Processing,2006,14(2):666-678.
[32]Narozny M,Barret M Dinh-Tuan Pham D T.ICA based algorithms for computing optimal 1-D linear block transforms in variable high-rate source coding.Signal Processing,2008,88(2):268-283.
[33]Pei S C,Zeng Y C.A novel image recovery algorithm for visible watermarked images.IEEE Transactions on Information Forensic and Security,2006,1(4):543-550.
[34]Wang F S,Li H W,Li R.Unified parametric and nonparametric ICA algorithms for hybrid source signals and stability analysis.International Journal of Innovative Computing,Information and Control,2008,4(4):933-942.
[35]Ranganathan R,Mikhael W B.A comparative study of complex gradient and fixed-point ICA algorithms for interference suppression in static and dynamic channels.Signal Processing,2008,88(2):399-406.
[36]Squartini S,Arcangeli A,Piazza F.Stability analysis of natural gradient learning rules in overdetermined ICA.Signal Processing,2008,88(3):761-766.
[37]Ye Y,Zhang Z L,Zeng J Z et al.A fast and adaptive ICA algorithm with its application to fetal electrocardiogram extraction.Applied Mathematics and Computation,2008,205(2):799-806.
[38]Lee I,Kim T,Lee T W.Fast fixed-point independent vector analysis algorithms for convolutive blind source separation.Signal Processing,2007,87(8):1859-1871.
[39]Hyv(a|¨)rinen A,Oja E.A fast fixed-point algorithm for independent component analysis.Neural Computation,1997,9(7):1483-1492.
[40]Hyv(a|¨)rinen A.Fast and robust fixed-point algorithms for independent component analysis.IEEE Transactions on Neural Networks,1999,10(3):626-634.
[41]Shen H,Kleinsteuber M,H(u|¨)per H.Local convergence analysis of fastICA and related algorithms.IEEE Transactions on Neural Networks,2008,19(6):1022-1032.
[42]Douglas S C,Gupta M,Sawada H et al.Spatio-temporal fastICA algorithms for the blind separation of convolutive mixtures.IEEE Transactions on Audio,Speech,and Language Processing,2007,15(5):1511-1520.
[43]谭文,王耀南.混沌系统的模糊神经网络控制理论与方法.北京:科学出版社,2008.
[44]焦李成,杨淑嫒.自适应多尺度神经网络理论与应用.北京:科学出版社,2008.
[45]Hopfield J J.Neural networks and physical systems with emergent collective computational abilities.Proceedings of the National Academy of Sciences,USA,1982,79:2554-2558.
[46]夏定纯,徐涛.计算智能.北京:科学出版社,2008.
[47]张仰森,黄改娟.人工智能教程.北京:高等教育出版社,2008.
[48]雷赟,刘建,严波等.窄带的自同步音频水印算法.计算机学报,2008,31(7):1283-1290.
[49]王虹,孙毅.基于水印序号的抗裁剪音频数字水印算法.武汉理工大学学报,2008,32(3):481-484.
[50]Foo S W,Xue F,Li M Y.A blind audio watermarking scheme using peak point extraction.IEEE International Symposium on Circuit and Systems,Kobe,Japan,2005:4409-4412.
[51]Ma X H,Zhang B,Ding X H.Self-synchronization blind audio watermarking based on feature extraction and subsampling.International Symposium on Neural Networks,Nanjing,China,2007.Berlin/Heidelberg:Springer,2007,4492:40-46.
[52] Wang S S, Tsai S L. Automatic image authentication and recovery using fractal code embedding and image inpainting. Pattern Recognition, 2008, 41(2): 701-712.
[53] Shih F Y, Wu Y T. Robust watermarking and compression for medical images based on genetic algorithms. Information Sciences, 2005, 175(3): 200-216.
[54] Mooney A, Keating J G, Heffernan D M. A detailed study of the generation of optically detectable watermarks using the logistic map. Chaos, Solitons & Fractals, 2006, 30(5):1088-1097.
[55] Xiang F, Qiu S S. Analysis on stability of binary chaotic pseudorandom sequence. IEEE Communications Letters, 2008, 12: 337-339.
[56] Tsuneda A, Mitsuishi S, Inoue T. A study on generation of random bit sequences with post-processing by linear feedback shift registers. International Journal of Innovative Computing, Information and Control, 2008, 4(10): 2631-2638.