期刊文献+

基于数据融合和ICA的鲁棒数字水印算法 被引量:2

Robust Digital Watermarking Algorithm Based on Data Fusion and ICA
下载PDF
导出
摘要 利用树状小波分解结合人类视觉系统的特性,提出一种基于数据融合的鲁棒性数字水印算法,可以向载体图像中自适应地嵌入多个数字水印副本。在每个块中使用独立分量分析的方法提取水印,对提取出的多个水印副本图像进行融合操作,以提高水印的鲁棒性。仿真试验表明,以该方法嵌入的水印具有较高的透明性,对常见图像处理攻击有很强的鲁棒性。 By using data fusion, this paper proposes a robust digital watermarking algorithm. Multiple copies of digital watermarking are embedded into the carrier image by exploiting the characteristics of tree-structured wavelet decomposition and human visual system, and Independent Component Analysis(ICA) method can be used to extract these copies. These extracted copies are fused by PCA image fusion algorithm so as to improve the robustness of the algorithm. Simulation experiments show that the scheme is effective, and achieves higher transparency and strong robustness to common image processing attacks.
出处 《计算机工程》 CAS CSCD 北大核心 2008年第10期150-152,157,共4页 Computer Engineering
基金 国家自然科学基金资助项目(60373062,60573045) 高校博士点基金资助项目(20050532007) 湖南省教育厅青年项目基金资助项目(04B016)
关键词 数字水印 树状小波分解 独立分量分析 数据融合 digital watermarking tree-structured wavelet decomposition Independent Component Analysis(ICA) data fusion
  • 相关文献

参考文献11

  • 1Peter H,Oscar C.A Novel Blind Multiple Watermarking Technique for Images[J].IEEE Trans.on Circuits and Systems for Video Technology,2003,13(8):813-830. 被引量:1
  • 2何柯峰,高隽,胡良梅,陆璐.一种基于主分量分析的融合识别方法[J].仪器仪表学报,2004,25(z3):440-442. 被引量:5
  • 3Chang Tianhong,Kou J.Texture Analysis and Classification with Tree-structured Wavelet Transform[J].IEEE Trans.on Image Processing,1993,2(4):429-441. 被引量:1
  • 4Wen Kuei-Ann.The Transform Image Codec Based on Fuzzy Control and Human Visual System[J].IEEE Trans.on Fuzzy Systems,1995,3(3):253-259. 被引量:1
  • 5Juliana F,Mark H.Multiscale Color Invariants Based on the Haman Visual System[J].IEEE Trans.on Image Processing,2001,10(11):1630-1638. 被引量:1
  • 6Mark D.Algorithms for Nonnegative Independent Component Analysis[J].IEEE Transtions on Neural Networks,2003,14(3):534-543. 被引量:1
  • 7Amari S,Cichocki A.Adaptive Blind Signal Processing[J].Proc.of IEEE,1998,86(10):2026-2048. 被引量:1
  • 8Wang Zhijun.A Comparative Analysis of Image Fusion Methods[J].IEEE Trans.on Geoscience and Remote Sensing,2005,43(6):1391-1402. 被引量:1
  • 9Kong Hui.Generalized 2D Principal Component Analysis[C]//Proc.of IEEE Int'l Conf.on Neural Networks.[S.1.]:IEEE Press,2005. 被引量:1
  • 10Chen Tung-Shou.A Combined K-means and Hierarchical Clustering Method for Improving the Clustering Efficiency of Microarray[C]//Proc.of IEEE Int'l Conf.on Intelligent Signal Processing and Communication Systems.[S.1.]:IEEE Press,2005. 被引量:1

二级参考文献8

  • 1郁文贤,雍少为,郭桂蓉.多传感器信息融合技术述评[J].国防科技大学学报,1994,16(3):1-11. 被引量:156
  • 2[3]焦李成.神经网络的应用与实现.西安:西安电子科技大学出版社,1996. 被引量:3
  • 3[3]Hu Liangmei, Gao Jun, Wang Andong, Hu Yong. A neural network shape recognition system based on D-S theory 2003 IEEE International Conference on Intelligent Transportation Systems, Shanghai, China, October 12- 15,2003,524~528. 被引量:1
  • 4[5]Lawrence A. Klein. Sensor and data fusion concepts and applications. SPIE Optical Engineering Press, 1999. 被引量:1
  • 5[7]Thierry Denoeux. A neural network classifier based on Dempster-Shafer theory. IEEE Trans. Syst. Man Cybern. , 2000,10(2) :131~150. 被引量:1
  • 6[12]Yong Hu, Jun Gao, Liang-Mei Hu, Huo-Ming Dong.A new method of determing the basic belief assignment in D-S evidence theory. The Second International Conference on Machine Learning and Cybernetics (ICMLC2003), Xi'an, China, Nov. 2003,3208~3212. 被引量:1
  • 7尹康,向辉,石教英.多媒体数据数字水印系统及其攻击分析[J].计算机科学,1999,26(10):44-48. 被引量:8
  • 8董火明,高隽,胡良梅,董文雯.基于主分量分析的形状特征提取及识别研究[J].合肥工业大学学报(自然科学版),2003,26(2):176-179. 被引量:25

共引文献37

同被引文献37

引证文献2

二级引证文献8

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部