Blind DT-CWT domain additive spread-spectrum watermark detection

In this paper, we adapt two blind detector structures for additive spread-spectrum image watermarking to the host signal characteristics of the dual-tree complex wavelet transform (DT-CWT) domain coefficients. The research is motivated by the superior perceptual characteristics of the DT-CWT and its active use in watermarking. To improve the numerous existing watermarking schemes in which the host signal is modeled by a Gaussian distribution, we show that the generalized Gaussian nature of dual-tree detail subband statistics can be exploited for better detector performance. We found that the Rao detector is more practical than the likelihood-ratio test for our detection problem. We experimentally investigate the robustness of the proposed detectors under JPEG and JPEG2000 attacks and assess the perceptual quality of the watermarked images. The results demonstrate that our alterations allow significantly better blind watermark detection performance in the DT-CWT domain than the widely used linear-correlation detector.