A HIERARCHICAL SPATIALLY ADAPTIVE IMAGE MODEL FOR PERCEPTUAL MASK DESIGN AND MULTIPLICATIVE WATERMARK DETECTION

In this work motivated by a hierarchical spatially adaptive image prior that we have developed for additive watermarking; we first, propose a new perceptual mask which improves robustness of additive watermark detectors in the spatial domain. The proposed mask is based on the local image variations along the two principal directions and enhances the watermark's energy while satisfying the imperceptibility requirement. Second we extent the application of the proposed hierarchical image prior for the multiplicative watermarking problem and we propose new watermark detectors. Numerical results are provided that demonstrate both the value of the proposed mask, and the improved sensitivity as compared to additive watermarking, with the same image model, of the proposed multiplicative watermark detector. Furthermore, we demonstrate its improved robustness compared to other state of the art similar in spirit watermark detectors.