期刊文献+

基于小波对比度和神经网络的图像隐写方法 被引量:2

Image Steganographic Method Based on Wavelet Contrast and Neural Networks
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摘要 为使通信安全在传输过程中提供较大的秘密信息嵌入量,并保持较好的载密图像质量,提出一种基于自组织特征映射神经网络和小波对比度的图像隐写方法。将载体图像分成固定大小的小块,采用小波一级分解并计算其小波对比度,利用自组织特征映射神经网络将小块分为3类,采用模算子技术嵌入秘密信息。实验结果表明,该方法有较大的嵌入量并保持良好的载密图像质量。 To provide larger capacity of the hidden secret data and to maintain a better visual quality of stego-image, this paper presents a image steganographic method based on Self-Organizing feature Map(SOM) neural networks and wavelet contrast. It divides an image into blocks, and decomposes every block into one-level wavelet to obtain the wavelet contrast. The method classifies blocks into 3 kindsby SOM, and embeds secret information with steganography, which is based on modulus. Experimental results show that the proposed method hides much more information and maintains a better visual quality of stego-image.
出处 《计算机工程》 CAS CSCD 北大核心 2010年第5期154-155,158,共3页 Computer Engineering
基金 湖南省教育厅科研基金资助项目(08C876)
关键词 隐写方法 自组织特征映射神经网络 小波对比度 steganographic method Self-Organizing feature Map(SOM) neural networks wavelet contrast
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参考文献9

  • 1Bender W, Gruhl D, Morimoto N, et al. Techniques for Data Hiding[J]. IBM System Journal, 1996, 35(3/4): 313-336.
  • 2Petitcolas F A P, Anderson R J, Kuhn M G. Information Hiding A Survey[J]. Proc. of the IEEE, 1999, 87(7): 1062-1078.
  • 3Kawaguchi E, Eason R O. Principle and Application of BPCS-steganography[C]//Proc. of Multimedia Systems and Applications Conference. Boston, USA: [s. n.], 1998:464 - 472.
  • 4Wu Dachun, Tsai W H. A Steganographic Method for Images by Pixel-value Differencing[J]. Pattern Recognition Letters, 2003, 24(10): 1613-1626.
  • 5Chang Chin-Chen, Tseng Hsien-Wen. A Steganographic Method for Digital Images Using Side Match[J]. Pattern Recognition Letters, 2004, 25(12): 1431-1437.
  • 6Zhang Xinpeng, Wang Shuozhong. Steganography Using Multiple-based Notational System and Human Vision Sensitivity[J]. IEEE Signal Processing Letters, 2005, 12(1): 67-70.
  • 7Kang Zhiwei, Liu Jin, He Yigang. Steganography Based on Self-organizing Competitive NNS and HVS[C]//Proc. of the 5th International Conference on Distributed Computing and Applications for Business, Engineering and Sciences. Shanghai, China: Shanghai University Press, 2006:395-397.
  • 8刘劲,康志伟,何怡刚.一种基于小波对比度和LSB的密写[J].电子学报,2007,35(7):1391-1393. 被引量:19
  • 9Thien Chih-Ching, Lin Ja-Chen. A Simple and High-hiding Capacity Method for Hiding Digit-by-digit Data in Images Based on Modulus Function[J]. Pattern Recognition, 2003, 36(12): 2875-2881.

二级参考文献10

  • 1杨志,毛士艺,陈炜.一种新的基于小波对比度的图像融合算法[J].系统工程与电子技术,2005,27(2):209-211. 被引量:15
  • 2Bender W,Gruhl D,Morimoto N,Lu A.Techniques for data hiding[J].IBM System Journal,1996,35(3,4):313-336.
  • 3Petitcolas F A P,Anderson R J,Kuhn M G.Information hiding-a survey[J].In Proc IEEE,1999,87(7):1062-1078.
  • 4Kawaguchi E,Eason R O.Principle and application of BPCS-steganography[A].In Proc SPIE:Multimedia Systems and Applications,3528[C].Boston:Massachusetts,1998.464-472.
  • 5Wu D C,Tsai W H.A steganographic method for images by pixel-value differencing[J].Pattern Recognition Letters,2003,24(10):1613-1626.
  • 6Zhang X,Wang S.Steganography using multiple-base notational system and human vision sensitivity[J].IEEE Signal Processing Letters,2005,12(1):67-70.
  • 7Toet A,Ruyven Lvan,Velaton J.Merging thermal and visual images by a contrast pyramid[J].Opt Engineering,1989,28(7):789-792.
  • 8Stephane Mallat著,杨力华等译.信号处理的小波引导[M].北京:机械工业出版社,2002.
  • 9Petitcolas FAP,Anderson RJ.Evaluation of copyright marking systems[A].In Proc IEEE Multimedia Systems[C].Italy:Florence,1999.574-579.
  • 10蒲恬,方庆喆,倪国强.基于对比度的多分辨图像融合[J].电子学报,2000,28(12):116-118. 被引量:92

共引文献18

同被引文献15

  • 1梁小萍,何军辉,李健乾,黄继武.隐写分析——原理、现状与展望[J].中山大学学报(自然科学版),2004,43(6):93-96. 被引量:12
  • 2康志伟,刘劲,何怡刚.基于HVS的抗统计分析的小波域密写[J].国防科技大学学报,2007,29(3):76-80. 被引量:2
  • 3Huang P, Harris C, Nixon M. Human Gait Recognition in Canonical Space Using Temporal Templates[J]. Vision Image and Signal Processing, 1999, 146(2): 93-100.
  • 4Bao Xuecai, Hu Jianfeng. Phase Synchronization for Classification of Motor imagery EEG[J]. Journal of Information & Computational Science, 2008, 5(2): 949-956.
  • 5Poulos M. On the Use of EEG Features Towards Person Identification via Neural Networks[J]. Medical Informatics & the Internet in Medicine, 2001,26(1): 35-48.
  • 6Pfurtscheller G. Motor Imagery and Direct Brain-cornputer Communication[J]. Proceedings of the IEEE, 2001, 89(7): 1123- 1134.
  • 7BARNI M, BARTOLIN1 F, PIVA A. Improved wavelet-based wa- termarking through pixel-wise masking [ J]. IEEE Transactions on linage Processing, 2001, 10(5) : 783 -791.
  • 8DO M N, VETI'ERLI M. The contourlet transform: an efficient di- rectional multiresolution image representation [ J]. IEEE Transac- tions on hnage Processing, 2005, 14( 12): 2091 -2106.
  • 9MATALON B, ELAD M, ZIBULEVSKY M. Improved denoising of images using modelling of a redundant contourlet transform [ C]// Proceedings of the SPIE Conference on Wavelets. Bellingham, WA: SPIE, 2005:617 - 628.
  • 10CAI X, ZHAO W. A novel algorithm for multifocus image fusion based on contourlet hidden Markov tree model [ C]// ICSP 2008: Proceedings of the 9th International Conference on Signal Process- ing. Piscataway: IEEE Press, 2008:1019-1022.

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