Statistical Watermark Detection in the Transform Domain for Digital Images

Abstract

The problem of multiplicative watermark detection in digital images can be viewed as a binary decision where the observation is the possibility that watermarked samples can be thought of as a noisy environment in which a desirable signal, called watermark, may exist. In this chapter, we investigate the optimum watermark detection from the viewpoint of decision theory. Different transform domains are considered with generalized noise models. We study the effect of the watermark strength on both the detector performance and the imperceptibility of the host image. Also, the robustness issue is addressed while considering a number of commonly used attacks.