期刊文献+

基于离散小波变换和离散余弦变换域的扩频水印盲提取算法 被引量:4

Blind extraction algorithm of spread-spectrum watermark based on discrete wavelet transform and discrete cosine transform domain
在线阅读 下载PDF
导出
摘要 针对扩频水印的盲提取问题,提出了一种在数字音频中扩频水印的盲提取算法。算法将扩频后的水印信息隐藏在音频文件小波分解的低频系数再做离散余弦变换(DCT)后的第5个系数中。提取时在扩频序列及其长度均未知的情况下,采用二次谱和奇异值分解(SVD)的方法对嵌入时使用的扩频参数进行估计,实现了数字音频中扩频水印的盲提取。仿真实验表明,所提算法在未知扩频参数的情况下能提取出归一化系数(NC)为1的水印图像并且水印的鲁棒性也很强,在加噪、低通滤波等攻击下估计出的扩频序列正确率能达到90%以上,恢复出的水印图像清晰可见,归一化系数都在0.98以上。 According to the blind extracting issues within the spread-spectrum watermark, a kind of blind extracting algorithm which could be used in the extraction of the digital audio signals was proposed. In the algorithm, wavelet transform was applied to the audio document, then the Discrete Cosine Transform (DCT) was used to its low-frequency coefficient. Afterwards, the fifth coefficient was got and it was used to hide the watermark information being spectrum spread. As the spread-spectrum sequence and its length were unknown during the extraction, spectrum-reprocessing and Singular Value Decomposition (SVD) were introduced to estimate the spread-spectrum using in the embedding process, and the blind extraction to the spread-spectrum watermark of the given digital signal was fulfilled. The simulation results show that with unknown spread-spectrum parameter, watermark image with Normalized Coefficient (NC) of one can be extracted, and it is of strong robustness. Under the attacks of noises and low-pass filter, the accuracy rate of the estimating spread-spectrum sequence is over 90%, which guarantees the recovery of clear water mark image with normalization coefficient higher than 0. 98.
出处 《计算机应用》 CSCD 北大核心 2013年第1期138-141,145,共5页 journal of Computer Applications
基金 国家自然科学基金资助项目(61071196 61102131) 教育部新世纪优秀人才支持计划项目(NCET-10-0927) 信号与信息处理重庆市市级重点实验室建设项目(CSTC2009CA2003) 重庆市杰出青年基金资助项目(CSTC2011jjjq40002) 重庆市自然科学基金资助项目(CSTC2009BB2287 CSTC2010BB2398 CSTC2010BB2409 CSTC2010BB2411)
关键词 离散小波变换 离散余弦变换 扩频水印 扩频序列 二次谱 奇异值分解 Discrete Wavelet Transform (DWT) Discrete Cosine Transform (DCT) spread-spectrum watermark spread-spectrum sequence spectrum-reprocessing Singular Value Decomposition (SVD)
作者简介 通信作者电子邮箱27588734@qq.com 胡然(1987-),女,重庆人,硕士研究生,主要研究方向:数字音频水印; 张天琪(1971-),男,四川眉山人,教授,主要研究方向:宽带微弱无线电信号处理、盲信号与信息处理、通信对抗理论与技术; 高洪兴(1987-),男,河北保定人,硕士研究生,主要研究方向:低信噪比WCDMA非盲检测与估计、盲检测与估计。
  • 相关文献

参考文献11

二级参考文献47

共引文献49

同被引文献45

  • 1MISHRA M,ADHIKARY F.Digital image tamper detection techniques-a comprehensive study[J].International Journal of Computer Science and Business Informatics,2013,2(1):73-85.
  • 2COX I J,KILIAN J,LEIGHTON F T,et al.Secure spread spectrum watermarking for multimedia[J].IEEE Transactions on Image Processing,1997,6(12):1673-1687.
  • 3NIKOLAIDIS N,PITAS I.Copyright protection of images using robust digital signatures[C]//Proceedings of the 1996 International Conference on Acoustics,Speech,and Signal Processing.Washington,DC:IEEE Computer Society,1996,4:2168-2171.
  • 4BATHSTI F,CARLI M,NERI A.Image forgery detection by means of no-reference quality metrics[C]//Proceedings of the 2012SPIE Conference on Media Watermarking,Security,and Forensics.Bellingham:SPIE,2012:8303-8317.
  • 5DOYODDORJ M,RHEE K.A blind forgery detection scheme using image compatibility metrics[C]//Proceedings of the 2013 IEEE International Symposium on Industrial Electronics.Piscataway:IEEE Press,2013:1-6.
  • 6CIPTASARI R W,RHEE K H,SAKURAI K.Image splicing verification based on pixel-based alignment method[C]//IMDW '12:Proceedings of the 11th International Conference on Digital Forensics and Watermarking.Berlin:Springer-Verlag,2013:198-212.
  • 7SHAO H,YU T,XU M,et al.Image region duplication detection based on circular window expansion and phase correlation[J].Forensic Science International,2012,222(1/2/3):71-82.
  • 8SHI Y Q,CHEN C,CHEN W.A natural image model approach to splicing detection[C]//MM&Sec '07:Proceedings of the 9th Workshop on Multimedia and Security.New York:ACM,2007:51-62.
  • 9Columbia DVMM Research Lab.Columbia image splicing detection evaluation dataset[EB/OL].[2013-05-10].http://www.ee.columbia.edu/ln/drmm/downloads/AuthSplicedDataSet/AuthSplicedDataSet.htm.
  • 10HE Z,LU W,SUN W,et al.Digital image splicing detection based on Markov features in DCT and DWT domain[J].Pattern Recognition,2012,45(12):4292-4299.

引证文献4

二级引证文献19

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