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    Robust multiplicative watermarking technique with Maximum Likelihood detector

    , Article 16th European Signal Processing Conference, EUSIPCO 2008, Lausanne, 25 August 2008 through 29 August 2008 ; 2008 ; 22195491 (ISSN) Sahraeian, S. M. E ; Akhaee, M. A ; Sankur, B ; Marvasti, F ; Canton de Vaud; Interactive Multimodal Information Management (IM); SIMILAR - Network of Excellence; Swiss National Science Foundation (SNSF ; Sharif University of Technology
    European Signal Processing Conference, EUSIPCO  2008
    Abstract
    In this paper, a new multiplicative semi-blind image-adaptive watermarking system has been presented, which exploits human visual model for adapting the watermark data to local properties of the host image. To have a better robustness, the proposed algorithm is implemented on the low-frequency coefficients of the wavelet transform. Moreover, regarding invisibility of the algorithm, the strength factor which controls the watermark power is optimally selected. To extract the watermark data, the Maximum Likelihood (ML) estimator is used. Experimental results confirm the imperceptibility of the proposed method and its high robustness against various attacks such as JPEG compression, noise... 

    Robust scaling-based image watermarking using maximum-likelihood decoder with optimum strength factor

    , Article IEEE Transactions on Multimedia ; Volume 11, Issue 5 , 2009 , Pages 822-833 ; 15209210 (ISSN) Akhaee, M. A ; Sahraeian, S. M. E ; Sankur, B ; Marvasti, F ; Sharif University of Technology
    2009
    Abstract
    In this paper, a new scaling-based image-adaptive watermarking system has been presented, which exploits human visual model for adapting the watermark data to local properties of the host image. Its improved robustness is due to embedding in the low-frequency wavelet coefficients and optimal control of its strength factor from HVS point of view. Maximum-likelihood (ML) decoder is used aided by the channel side information. The performance of the proposed scheme is analytically calculated and verified by simulation. Experimental results confirm the imperceptibility of the proposed method and its higher robustness against attacks compared to alternative watermarking methods in the literature.... 

    Estimation of data hiding capacity of digital video based on human visual model in temporal domain

    , Article 2nd International Conference on Signal Processing and Communication Systems, ICSPCS 2008, Gold Coast, QLD, 15 December 2008 through 17 December 2008 ; April , 2008 ; 9781424442423 (ISBN) Khalilian, H ; Ghaemmaghami, S ; Sharif University of Technology
    2008
    Abstract
    A new approach to evaluation of the data hiding capacity of digital video is presented in this paper. The paper reconsiders the conventional capacity estimation algorithms, in which the video signal is taken as a sequence of still images, that result in an exaggerated upper bound of hiding capacity or a much higher value than the actual embedding capacity. The proposed method for the capacity estimation is based on the human visual model in temporal domain, which leads to a more realistic, tighter bound for video capacity. In this method, according to temporal characteristic of every frame, a visibility based coefficient is extracted that is used to determine the hiding capacity. The maximum...