Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/70891
Title: Maximum likelihood detection in image watermarking using generalized gamma model
Authors: Ng, T.M. 
Garg, H.K. 
Issue Date: 2005
Source: Ng, T.M.,Garg, H.K. (2005). Maximum likelihood detection in image watermarking using generalized gamma model. Conference Record - Asilomar Conference on Signals, Systems and Computers 2005 : 1680-1684. ScholarBank@NUS Repository.
Abstract: Digital image watermark can be detected in transform domain using maximum likelihood (ML) detection, whereby the decision threshold is obtained using the NeymanPearson criterion. A probability distribution function (PDF) is required to correctly model the statistical behavior of the transform coefficients. In the literature, this detection method has been considered by modeling magnitude of a set of discrete Fourier transform (DFT) coefficients using a Weibull PDF. In this paper, we propose extending the Weibull model to a generalized gamma model. For the work here, we also propose new estimators for parameters of the generalized gamma PDF. © 2005 IEEE.
Source Title: Conference Record - Asilomar Conference on Signals, Systems and Computers
URI: http://scholarbank.nus.edu.sg/handle/10635/70891
ISBN: 1424401313
ISSN: 10586393
Appears in Collections:Staff Publications

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