Abstract
A perceptual pyramid watermarking method is proposed. The key idea is to use the contrast sensitivity of the human visual system (HVS) to determine “invisible” regions where watermark energy can be adjusted providing an invisible and robust watermark. These invisibles regions are obtained by computing a “visibility map” at each level of the Gaussian pyramid (GP). The watermark is weighted by the local contrast and a global scaling factor. The embedding process is performed by modifying the values in some levels of the Laplacian Pyramid (LP) using the spread spectrum technique. Afterwards, the watermarked image can be constructed from the levels of the LP. For watermark detection, a blind detection scheme using the threshold-correlation based technique is proposed. Finally, the performances of the watermarking method are evaluated in terms of invisibility and robustness using some quality metrics and different attacks of Stirmark such as Gaussian noise, low-pass filtering, Jpeg compression and cropping. This evaluation is performed for the choice of some parameters of the watermarking system depending on performances such as invisibility and robustness. The design of our watermarking technique can finally be formulated as an optimisation problem where the objective is to guarantee a trade-off between invisibility and robustness.
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Wolfgang R.B., Podilchuk C.I., Delp E.J.: Perceptual watermarks for digital images and video. Proc. IEEE 87(X), 1108–1126 (1999)
Poldichuck C.I., Zeng W.: Image-adaptive watermarking using visual models. IEEE J. Sel. Areas Commun. 16, 525–539 (1998)
Langelaar G.C., Setyawan I., Lagendijk R.: Watermarking digital image and video data. A state-of-the-art overview. IEEE Signal Process. Mag. 17, 20–46 (2000)
Bergman C., Davidson J.: Unitary embedding for data hiding with the SVD. Secur. Steganography Watermarking Multimed. Contents VII, SPIE 5681, 619–630 (2005)
Miller M.L., Doerr G.J., Cox I.J.: Applying informed coding and embedding to design a robust, high capacity watermark. IEEE Trans. Image Process. 13(6), 792–807 (2004)
Fechner, G.T.: Elemente der psychophysic. Vol. 2, Chap. XVI, Breitkopf und Härtel, Leipzig (1860)
Moon P., Spencer D.E.: The visual effect of non uniform surrounds. J. Opt. Soc. Am. A 35, 233–248 (1945)
Peli E.: Contrast in complex images. J. Opt. Soc. Am. A 7, 2032–2040 (1990)
Yee Y.H.: A perceptual metric for production testing. J. Graph. GPU Game Tools 9, 33–40 (2004)
Kundur D., Hatzinakos D.: A robust digital image watermarking method using wavelet-based fusion. Proc. Int. Conf. Image Process. 1, 544–547 (1997)
Kutter M., Winkler S.: A vision-based masking model for spread-spectrum image watermarking. IEEE Trans. Image Process. 11, 16–25 (2002)
Masry M., Chandler D., Hemami S.S.: Digital watermarking using local contrast-based texture masking. Conf. Signals Syst. Comput. Conf. Rec. Thirty-Seventh Asilomar 2, 1590–1594 (2003)
Zhang X., Lin W., Xue P.: Improved estimation for just-noticeable visual distortion. Signal Process. 85(4), 795–808 (2005)
Burt P.J., Adelson E.H.: The Laplacian pyramid as a compact image code. IEEE Trans. Commun. 31, 532–540 (1983)
Belkacem-Boussaid K., Beghdadi A.: A new image smoothing method based on a simple model of spatial processing in the early stages of human vision. IEEE Trans. Image Process. 9, 220–226 (2000)
Iordache R., Beghdadi A., Viaris de Lesengno P.: Pyramidal perceptual filtering using moon and spencer contrast. Proc. Int. Conf. Image Process. 3, 146–149 (2001)
Shnayderman A., Gusev A., Eskicioglu A.M.: A multidimensional image quality measure using singular value decomposition. Proc. SPIE Image Quality Syst. Perform. Conf. San Jose, CA 5294, 82–92 (2004)
Beghdadi A., Pesquet-Popescu B.: A new image distortion measure based on wavelet decomposition. Proc. IEEE ISSPA Paris, France 2, 485–488 (2003)
Wang Z., Bovik A.C., Sheikh H.R., Simoncelli E.P.: A universal image quality index. IEEE Signal Process. Lett. 9, 81–84 (2002)
Beghdadi, A.: Design of an image distortion measure using spatial/spatial-frequency analysis. The First 2004 IEEE-EURASIP International Symposium on Control, Communications and Signal Processing, Hammamet, Tunisia on March 21–24, 2004, Invited (2004)
Piva, A., Barni, M., Bartolini, F., Cappellini, V.: Threshold selection for correlation-based watermark detection. Proceedings of COST 254 Workshop on Intelligent Communications pp. 66–72. (1998)
Kutter M., Winkler S.: A vision-based masking model for spread-spectrum image watermarking. IEEE Trans. Image Process. 11, 16–25 (2002)
Kundur D., Hatzinakos D.: A robust digital image watermarking method using wavelet-based fusion. IEEE-ICIP 1, 544–547 (1997)
Wolfgang R.B., Podilchuk C.I., Delp E.J.: Perceptual watermarks for digital images and video. Proc. IEEE 87, 1108–1126 (1999)
Stirmark benchmark 4.0, http://www.petitcolas.net/fabien/watermarking/stirmark/
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Luong, M., Do, Q.B. & Beghdadi, A. A blind image watermarking using multiresolution visibility map. J Glob Optim 49, 435–448 (2011). https://doi.org/10.1007/s10898-010-9570-4
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DOI: https://doi.org/10.1007/s10898-010-9570-4