Optimum detection for Barni's multiplicative watermarking in DWT domain

With the increasing demands of copyright protection, watermarking technology has being paid more and more attention. In the design of watermarking algorithm, a good watermark detection scheme can improve the successful detection rate, which pushes more and more researchers to work on optimum detectors. In this paper, with respect to Barni's multiplicative watermarking that is based on human visual system (HVS), the optimum detection using Bayesian decision rule is firstly proposed. The decision threshold is obtained by the NP criterion. The probability density function of the transform coefficients is modeled by using the generalized Gaussian distribution. Its simplification equation is given using Gaussian distribution. It can result in a better performance than correlation detection.