Efficient detection of additive watermarking in the DWT-domain

This paper aims at efficient, blind detection of additive spread-spectrum watermarks in the DWT domain. In our approach, the marginal distributions of the DWT detail subband coefficients are modeled either by the Generalized Gaussian distribution or by the recently proposed one-parameter Cauchy distribution. We investigate the computational demands for parameter estimation, hypothesis testing and threshold selection. Further, we discuss the tradeoff between computation time and detection accuracy.