Dct/dwt blind multiplicative watermarking through student-t distribution
Antonis Mairgiotis, Lisimachos Paul Kondi, Yongyi Yang · 2017
In this work, which addresses issues related to the efficient hiding of watermark information in the transform domain, we propose to model the transform coefficients with the Student-t distribution through the multiplicative rule of embedding. Based on the observation that the statistical distribution of the transform coefficients has heavy tailed behavior, we design a new class of watermark detectors following the multiplicative rule of embedding. We present experimental results that compare the proposed method with known state-of-the-art multiplicative watermark detectors and demonstrate its effectiveness in terms of sensitivity and robustness.