Image watermark detection in the wavelet domain using Bessel K densities

Abstract

In this study, the authors propose a wavelet domain still image watermark detection method which uses the Bessel K probability density function to describe the distribution of wavelet coefficients. In this study, watermark detection is formulated as a binary statistical decision problem which is to detect a signal submerged in the noise that follows a Bessel K distribution. Using this formulation, an optimal watermark detector using likelihood ratio test is proposed. The experimental results of the proposed method in a variety of situations demonstrate that the proposed method has a robust detection performance for additive spread spectrum watermarks.