Adaptive quantization watermarking

Abstract

Although quantization index modulation (QIM) schemes are optimal from an information theoretic capacity-maximization point of view, their robustness may be too restricted for widespread practical usage. Most papers assume that host signal samples are identically distributed from a single source distribution and therefore, they do not need to consider local adaptivity. In practice there may be however several reasons for introducing locally varying watermark parameters. In this paper, we study how the Scalar Costa Scheme (which we take as a representative member of the class of QIM schemes) can be adapted to achieve practical levels of robustness and imperceptibility. We do this by choosing the basic watermark parameters on the basis of a perceptual model. An important aspect is the robustness of the statistic on which the adaptation rule is based. The detector needs to be able to accurately re-estimate the value of the parameters as used by the embedder, even in the presence of strong channel noise. One way to achieve this is to base the adaptation rule on an aggregate of the pixel values in a neighborhood around the relevant pixel. We present an analysis of the robustness-locality trade-off, based on a model for the bit error probability.