Nonadditive Gaussian watermarking and its application to wavelet-based image watermarking

This paper extends our game-theoretic approach to design and embed watermarks in Gaussian signals in the presence of an adversary. The detector solves a binary hypothesis testing problem. The system is designed to minimize probability of error under the worst-case attack in a prescribed class of attacks. The embedder is allowed to filter the host signal and add a watermark, thereby making the scheme nonadditive. The theory is applied to wavelet-based image watermarking. We find that, in this framework, additive watermarks are clearly suboptimal.