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Zarmehi, N., Aref, M. (2016). Optimum decoder for multiplicative spread spectrum image watermarking with Laplacian modeling. The ISC International Journal of Information Security, 8(2), 131-139. doi: 10.22042/isecure.2016.8.2.4
N. Zarmehi; M. R. Aref. "Optimum decoder for multiplicative spread spectrum image watermarking with Laplacian modeling". The ISC International Journal of Information Security, 8, 2, 2016, 131-139. doi: 10.22042/isecure.2016.8.2.4
Zarmehi, N., Aref, M. (2016). 'Optimum decoder for multiplicative spread spectrum image watermarking with Laplacian modeling', The ISC International Journal of Information Security, 8(2), pp. 131-139. doi: 10.22042/isecure.2016.8.2.4
Zarmehi, N., Aref, M. Optimum decoder for multiplicative spread spectrum image watermarking with Laplacian modeling. The ISC International Journal of Information Security, 2016; 8(2): 131-139. doi: 10.22042/isecure.2016.8.2.4

Optimum decoder for multiplicative spread spectrum image watermarking with Laplacian modeling

Article 5, Volume 8, Issue 2 - Serial Number 1, Summer and Autumn 2016, Page 131-139  XML PDF (2003 K)
Document Type: ORIGINAL RESEARCH PAPER
DOI: 10.22042/isecure.2016.8.2.4
Authors
N. Zarmehi 1; M. R. Aref2
1Electrical Engineering Department, Sharif University of Technology, Tehran, Iran Advanced Communications Research Institute, Sharif University of Technology, Tehran, Iran
2Electrical 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
Laplacian Distribution; Maximum Likelihood Decoding; Spread Spectrum Method; watermarking
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