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Mathematical Problems in Engineering
Volume 2016 (2016), Article ID 4065215, 18 pages
http://dx.doi.org/10.1155/2016/4065215
Research Article

NSCT Domain Additive Watermark Detection Using RAO Hypothesis Test and Cauchy Distribution

1School of Electrical Information Engineering, Northeast Petroleum University, Daqing 163318, China
2College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China

Received 13 September 2015; Revised 1 February 2016; Accepted 15 February 2016

Academic Editor: Erik Cuevas

Copyright © 2016 Hongbo Bi et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. H. Bi, Y. Zhang, and X. Li, “Video watermarking using spatio-temporal masking for ST-DM,” Applied Mathematics and Information Sciences, vol. 7, no. 2, pp. 493–498, 2013. View at Publisher · View at Google Scholar · View at Scopus
  2. X. Wang, Y. Liu, S. Li, H. Yang, and P. Niu, “Robust image watermarking approach using polar harmonic transforms based geometric correction,” Neurocomputing, vol. 174, pp. 627–642, 2016. View at Publisher · View at Google Scholar
  3. Y. F. Zhu, “A robust blind image watermarking based on generalized Gaussian distribution,” Information Technology Journal, vol. 13, no. 7, pp. 1427–1430, 2014. View at Google Scholar
  4. C.-H. Chen, Y.-L. Tang, C.-P. Wang, and W.-S. Hsieh, “A robust watermarking algorithm based on salient image features,” Optik, vol. 125, no. 3, pp. 1134–1140, 2014. View at Publisher · View at Google Scholar · View at Scopus
  5. L. N. Chen, G. B. Yang, and N. B. Zhu, “A Cauchy distribution-based ternary hypothesis testing for bipolar additive watermark detection in H.264/AVC video,” The Imaging Science Journal, vol. 61, no. 3, pp. 301–310, 2013. View at Publisher · View at Google Scholar
  6. S. Fazli and M. Moeini, “A robust image watermarking method based on DWT, DCT, and SVD using a new technique for correction of main geometric attacks,” Optik, vol. 127, no. 2, pp. 964–972, 2016. View at Publisher · View at Google Scholar
  7. J. R. Hernández, M. Amado, and F. Pérez-González, “DCT-domain watermarking techniques for still images: detector performance analysis and a new structure,” IEEE Transactions on Image Processing, vol. 9, no. 1, pp. 55–68, 2000. View at Publisher · View at Google Scholar · View at Scopus
  8. A. Nikolaidis and I. Pitas, “Asymptotically optimal detection for additive watermarking in the DCT and DWT domains,” IEEE Transactions on Image Processing, vol. 12, no. 5, pp. 563–571, 2003. View at Publisher · View at Google Scholar · View at Scopus
  9. I. W. Selesnick, R. G. Baraniuk, and N. G. Kingsbury, “The dual-tree complex wavelet transform,” IEEE Signal Processing Magazine, vol. 22, no. 6, pp. 123–151, 2005. View at Publisher · View at Google Scholar · View at Scopus
  10. E. Le Pennec and S. Mallat, “Sparse geometric image representations with bandelets,” IEEE Transactions on Image Processing, vol. 14, no. 4, pp. 423–438, 2005. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  11. M. N. Do and M. Vetterli, “The contourlet transform: an efficient directional multiresolution image representation,” IEEE Transactions on Image Processing, vol. 14, no. 12, pp. 2091–2106, 2005. View at Publisher · View at Google Scholar · View at Scopus
  12. A. L. da Cunha, J. Zhou, and M. N. Do, “The nonsubsampled contourlet transform: theory, design, and applications,” IEEE Transactions on Image Processing, vol. 15, no. 10, pp. 3089–3101, 2006. View at Publisher · View at Google Scholar · View at Scopus
  13. H. Sadreazami, A. M. Omair, and M. N. S. Swamy, “Optimum multiplicative watermark detector in contourlet domain using the normal inverse Gaussian distribution,” in Proceedings of the IEEE International Symposium on Circuits and Systems (ISCAS '15), vol. 2015, pp. 1050–1053, Lisbon, Portugal, May 2015. View at Publisher · View at Google Scholar
  14. A. Khawne, B. Attachoo, and K. Hamamoto, “Optimum watermark detection of ultrasonic echo medical images,” IEEJ Transactions on Electrical and Electronic Engineering, vol. 10, no. 2, pp. 149–156, 2015. View at Publisher · View at Google Scholar · View at Scopus
  15. Q. Wang, W. J. Zeng, and J. Tian, “A compressive sensing based secure watermark detection and privacy preserving storage framework,” IEEE Transactions on Image Processing, vol. 23, no. 3, pp. 1317–1328, 2014. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  16. P. Comesaña, N. Merhav, and M. Barni, “Asymptotically optimum universal watermark embedding and detection in the High-SNR regime,” IEEE Transactions on Information Theory, vol. 56, no. 6, pp. 2804–2815, 2010. View at Publisher · View at Google Scholar
  17. A. Mairgiotis, L. Kondi, and Y. Yang, “Locally optimum detection for additive watermarking in the DCT and DWT domains through non-Gaussian distributions,” in Proceedings of the 18th International Conference on Digital Signal Processing (DSP '13), pp. 1–6, Santorini, Greece, July 2013. View at Publisher · View at Google Scholar · View at Scopus
  18. M. Mundher, D. Muhamad, A. Rehman, T. Saba, and F. Kausar, “Digital watermarking for images security using discrete slantlet transform,” Applied Mathematics & Information Sciences, vol. 8, no. 6, pp. 2823–2830, 2014. View at Publisher · View at Google Scholar · View at Scopus
  19. H. Sadreazami, M. O. Ahmad, and M. N. Swamy, “A study of multiplicative watermark detection in the contourlet domain using alpha-stable distributions,” IEEE Transactions on Image Processing, vol. 23, no. 10, pp. 4348–4360, 2014. View at Publisher · View at Google Scholar · View at MathSciNet
  20. Q. Cheng and T. S. Huang, “An additive approach to transform-domain information hiding and optimum detection structure,” IEEE Transactions on Multimedia, vol. 3, no. 3, pp. 273–284, 2001. View at Publisher · View at Google Scholar · View at Scopus
  21. R. Kwitt, P. Meerwald, and A. Uhl, “Blind DT-CWT domain additive spread-spectrum watermark detection,” in Proceedings of the 16th International Conference on Digital Signal Processing (DSP '09), pp. 1–8, IEEE, July 2009. View at Publisher · View at Google Scholar · View at Scopus
  22. X. Yin, S. Peng, and X. Zhu, “Detection for multiplicative watermarking in DCT domain by cauchy model,” in Information and Communications Security, pp. 173–183, Springer, Berlin, Germany, 2011. View at Google Scholar
  23. R. Kwitt, P. Meerwald, and A. Uhl, “Lightweight detection of additive watermarking in the DWT-domain,” IEEE Transactions on Image Processing, vol. 20, no. 2, pp. 474–484, 2011. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  24. A. Briassouli, P. Tsakalides, and A. Stouraitis, “Hidden messages in heavy-tails: DCT-domain watermark detection using alpha-stable models,” IEEE Transactions on Multimedia, vol. 7, no. 4, pp. 700–715, 2005. View at Publisher · View at Google Scholar · View at Scopus
  25. N. Merhav and E. Sabbag, “Optimal watermark embedding and detection strategies under limited detection resources,” IEEE Transactions on Information Theory, vol. 54, no. 1, pp. 255–274, 2008. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  26. R. J. Clarke, Transform Coding of Images, Academic Press, 1985.
  27. S. Nadarajah, “A generalized normal distribution,” Journal of Applied Statistics, vol. 32, no. 7, pp. 685–694, 2005. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet · View at Scopus
  28. M. K. Varanasi and B. Aazhang, “Parameteric generalized Gaussian density estimation,” Journal of the Acoustical Society of America, vol. 86, no. 4, pp. 1404–1415, 1989. View at Publisher · View at Google Scholar
  29. M. N. Do and M. Vetterli, “Wavelet-based texture retrieval using generalized Gaussian density and Kullback-Leibler distance,” IEEE Transactions on Image Processing, vol. 11, no. 2, pp. 146–158, 2002. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus