Samia Belkacem, Zohir Dibi, and Ahmed Bouridane


  1. [1] R.B. Wolfgang and C.I. Podilchuk, Perceptual watermarks for digital images and video, Proceedings of the IEEE, 87, 1999, 1108–1126.
  2. [2] R. Kwitt, P. Meerwald, and A. Uhl, Lightweight detection of additive watermarking in the DWT–Domain, IEEE Transactions on Image Processing, 20(2), 2010, 474–484.
  3. [3] X. Yin, S. Peng, and X. Zhu, in S. Qing, et al. (eds.), Detection for multiplicative watermarking in DCT domain by Cauchy model (Berlin, Heidelberg: Springer-Verlag, 2011), 173–183.
  4. [4] A. Louchene and A. Dahmani, Watermarking method resilient to rst and compression based on Dwt, LPM and phase correlation, International Journal of Computers and Applications, 35(1), 2013, 1–8.
  5. [5] A. Nikolaidis and I. Pitas, Comparison of different chaotic maps with application to image watermarking, IEEE Int. Symp. on Circuits and Systems, Geneva, Switzerland, 2000, 509–512.
  6. [6] Z. Dawei, C. Guanrong, and L. Wenbo, A chaos-based robust wavelet-domain watermarking algorithm, Chaos, Solitons and Fractals, 22, 2004, 47–54.
  7. [7] A. Mooney, A. Keating, and J. Pitas. A comparative study of chaotic and white noise signals in digital watermarking, Chaos, Solitons and Fractals, 35, 2008, 913–921.
  8. [8] K. Veeraswamy, Adaptive AC-coefficient prediction for image compression and blind watermarking, Journal of Multimedia, 3(1), 2008, 16–22.
  9. [9] D.Y. Gang, C. Ying, W.L. Feng, and Y. Zheng, Distributions of the DCT coefficient for watermark detection, Int. Conf. on Computer Application and System Modeling ICCASM, 13, Taiyuan, 22–24 Oct. 2010, 96–98.
  10. [10] F. Muller, Distribution shape of two-dimensional DCT coefficients of natural images, Electronic Letters, 28(22), 1993, 1935–1936.
  11. [11] R.J. Joshi and T.R. Fischer, Comparison of generalizedGaussian and Laplacian modeling in DCT image coding, IEEETransactions on Signal Processing Letters, 2, 1995, 81–82.
  12. [12] J.H. Chang, J.W. Shin, N.S. Kim, and S.K. Mitra, Imageprobability distribution based on generalized gamma function, IEEE Signal Processing Letters, 12(4), 2005, 325–328.
  13. [13] E.W. Stacy, A generalization of the Gamma distribution, Annals of Mathematical Statistics, 33(3), 1962, 1187–1192.
  14. [14] J.W. Shin, J.H. Chang, and N.S. Kim, Statistical modeling of speech signals based on generalized gamma distribution, IEEE Signal Processing Letters, 12(3), 2005, 258–262.
  15. [15] T.M. Ng and H. K. Garg, Maximum likelihood detection in image watermarking using generalized Gamma model, Proc.39th Asilomar Conf. on Signals, Systems, Computers, PacificGrove, CA, 2005, 1680–1684.
  16. [16] H.C. Li, W. Hong, Y.R. Wu, and P.Z. Fan, On the empirical-statistical modeling of SAR images with generalized gamma distribution, IEEE Journal of Selected Topics in Signal Processing, 5(3), 2011, 386–397.
  17. [17] G. Almpanidis and C. Kotropoulos, Phoneme segment boundary detection based on the generalized gamma distribution, Speech Communication, 50, 2008, 38–55.
  18. [18] A. Noufaily and M.C. Jones, On maximization of the likelihood for the generalized gamma distribution, Computational Statistics, 28, 2013, 505–517.
  19. [19] C.H. Yuen and K.W. Wong, A chaos-based joint image compression and encryption scheme using DCT and SHA-1, Applied Soft Computing, 11, 2011, 5092–5098.
  20. [20] J. Wang, B.G. Liub, Y. Daib, J. Sunb, Z. Wangb, and S.Lian, Locally optimum detection for Barni’s multiplicativewatermarking in DWT domain, Signal Processing, 88, 2008,117–130.
  21. [21] R. Kwitt, P. Meerwald, and A. Uhl, Efficient detection of additive watermarking in the dwt-domain, Eur. Signal Processing Conf. EUSIPCO 17, Glasgow, UK, August 24–28, 2009, 2072–2076.
  22. [22] N.V. Rao and V.M. Kumari, Watermarking in medical imaging for security and authentication, Information Security Journal: A Global Perspective, 20, 2011, 148–155.

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