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|Title:||Maximum likelihood detection in image watermarking using generalized gamma model||Authors:||Ng, T.M.
|Issue Date:||2005||Citation:||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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