A new statistical detector for CT-based multiplicative image watermarking using the t location-scale distribution

Abstract

In this study, a new statistical multiplicative watermark detector in contourlet domain is presented. The contourlet coefficients of images are highly non-Gaussian and a proper distribution to model the statistics of the contourlet coefficients is a heavy-tail Probability Distribution Function (PDF). In this study, a multiplicative watermarking scheme is proposed in the contourlet domain using t location-scale distribution (tLS). Afterward, we used the likelihood ratio decision rule and tLS distribution to design an optimal multiplicative watermark detector. The detector showed higher efficiency than other watermarking schemes in the literature, based on the experimental results, and its robustness against different attacks was verified.