A Cauchy distribution-based ternary hypothesis testing for bipolar additive watermark detection in H.264/AVC video

Abstract

The statistical distribution of discrete cosine transform (DCT) coefficients is important for video watermarking since they are the main carriers for watermark embedding. For the statistical distribution of intra-coded DCT coefficients in the H.264/AVC video stream, non-parametric hypothesis test is utilised to verify that Cauchy distribution is better than generalised Gaussian distribution (GGD). Moreover, ternary hypothesis test is introduced into the detection of bipolar additive watermarks. By adjusting the watermark strength parameter, the detector performance can be guaranteed. Experimental results show that for those bipolar additive watermarks in the H.264/AVC stream, the proposed approach can achieve a detection accuracy of more than 80% on average.