Optimum decoder for multiplicative spread spectrum image watermarking with Laplacian modeling

Document Type: ORIGINAL RESEARCH PAPER

Authors

1 Electrical Engineering Department, Sharif University of Technology, Tehran, Iran Advanced Communications Research Institute, Sharif University of Technology, Tehran, Iran

2 Electrical Engineering Department, Sharif University of Technology, Tehran, Iran Information Systems and Security Lab. (ISSL), Electrical Engineering Department, Sharif University of Technology, Tehran, Iran

Abstract

This paper investigates the multiplicative spread spectrum watermarking method for the image. The information bit is spreaded into middle-frequency Discrete Cosine Transform (DCT) coefficients of each block of an image using a generated pseudo-random sequence. Unlike the conventional signal modeling, we suppose that both signal and noise are distributed with Laplacian distribution, because the sample loss of digital media can be better modeled with this distribution than the Gaussian one. We derive the optimum decoder for the proposed embedding method thanks to the maximum likelihood decoding scheme. We also analyze our watermarking system in the presence of noise and provide analytical evaluations and several simulations. The results show that it has the suitable performance and transparency required for watermarking applications.

Keywords

References

[1] I. Cox, M. Miller, J. Bloom, J. Fridrich, and T. Kalker. Digital Watermarking and Steganography. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, 2008.

[2] M. A. Akhaee and F. Marvasti. A survey on digital data hiding schemes: Principals, algorithms, and applications. The ISC International Journal of Information Security, 5(1):5-36, January 2013.

[3] I. J. Cox, J. Kilian, F. T. Leighton, and T. Shamoon. Secure spread spectrum watermarking for multimedia. IEEE Transactions on Image Processing, 6(12):1673-1687, December 1997.

[4] N. Zarmehi and M. A. Akhaee. Video steganalysis of multiplicative spread spectrum steganography. In Proceedings of the 22nd European Signal Processing Conference (EUSIPCO), pages 2440-2444, September 2014.

[5] N. Zarmehi and M. A. Akhaee. Digital video steganalysis toward spread spectrum data hiding. IET Image Processing, 10(1):1-8, 2016.

[6] A. Nikolaidis and I. Pitas. Asymptotically optimal detection for additive watermarking in the dct and dwt domains. IEEE Transactions on Image Processing, 12(5):563-571, May 2003.

[7] A. Zaidi, R. Boyer, and P. Duhamel. Audio watermarking under desynchronization and additive noise attacks. IEEE Transactions on Signal Processing, 54(2):570-584, Feb 2006.

[8] X. Huang and B. Zhang. Robust detection of additive watermarks in transform domains. Information Security, IEE Proceedings, 153(3):97-106, Sept 2006.

[9] J. R. Hernandez, M. Amado, and F. PerezGonzalez. Dct-domain watermarking techniques for still images: detector performance analysis and a new structure. IEEE Transactions on Image Processing, 9(1):55-68, Jan 2000.

[10] A. Briassouli, P. Tsakalides, and A. Stouraitis. Hidden messages in heavy-tails: Dct-domain watermark detection using alpha-stable models. IEEE Transactions on Multimedia, 7(4):700-715, Aug 2005.

[11] J. Zhong and S. Huang. An enhanced multiplicative spread spectrum watermarking scheme. IEEE Transactions on Circuits and Systems for Video Technology, 16(12):1491-1506, Dec 2006.

[12] P. Campisi, D. Kundur, and A. Neri. Robust digital watermarking in the ridgelet domain. IEEE Signal Processing Letters, 11(10):826-830, Oct 2004.

[13] M. Barni, F. Bartolini, A. D. Rosa, and A. Piva. Optimum decoding and detection of multiplicative watermarks. IEEE Transactions on Signal Processing, 51(4):1118-1123, Apr 2003.

[14] D. Kirovski and H. S. Malvar. Spread-spectrum watermarking of audio signals. IEEE Transactions on Signal Processing, 51(4):1020-1033, Apr 2003.

[15] A. Valizadeh and Z. J. Wang. An improved multiplicative spread spectrum embedding scheme for data hiding. IEEE Transactions on Information Forensics and Security, 7(4):1127-1143, Aug 2012.

[16] M. A. Akhaee, N. K. Kalantari, and F. Marvasti. Robust audio and speech watermarking using gaussian and laplacian modeling. Signal Processing, 90(8):2487-2497, 2010.

[17] Xiang Yin, Shuoling Peng, and Xinshan Zhu. Detection for Multiplicative Watermarking in DCT Domain by Cauchy Model, pages 173-183. Springer Berlin Heidelberg, Berlin, Heidelberg, 2011.

[18] B. Mathon, F. Cayre, P. Bas, and B. Macq. Optimal transport for secure spread-spectrum watermarking of still images. IEEE Transactions on Image Processing, 23(4):1694-1705, April 2014. ISSN 1057-7149.

[19] N. Zarmehi, M. Banagar, and M. A. Akhaee. Optimum decoder for an additive video watermarking with laplacian noise in h.264. In International ISC Conference on Information Security and Cryptology (ISCISC), pages 1-5, August 2013.

[20] S. Farsiu, D. Robinson, M. Elad, and P. Milanfar. Robust shift and add approach to super resolution. In Society of Photo-Optical Instrumentation Engineering, volume 5203, pages 121-130, 2003.

[21] R. J. Marks, G. L. Wise, D. G. Haldeman, and J. L. Whited. Detection in laplace noise. IEEE Transactions on Aerospace and Electronic Systems, AES-14:866-872, 1978.

[22] R. J. Clarke. Transform Coding of Images. New York: Academic, 1985.

[23] T.-H. Kim, H. Adeli, C. Ramos, and B.-H. Kang. Signal processing, image processing and pattern recognition. Springer, Berlin, 2011.

The ISC International Journal of Information Security

Volume 8, Issue 2 - Serial Number 1
Summer and Autumn 2016
Pages 131-139

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