Optimal detection of multiplicative watermarks in Laplacian channels

In this work, we propose a model for an optimal detector of digital watermarks for Laplacian channels, the watermark embedding algorithm is the multiplicative embedding rule in time domain, the optimal detection equation and the threshold equation are derived using maximum likelihood (ML) and Neyman-Pearson criterion. The resulting system is blind and has very low complexity. Computer simulations are carried out applying the proposed model to audio signals and results prove that the proposed system is able to detect watermarks even if the watermarked object was severely attacked by noise, low pass filtering among other attacks.