Parameter Estimations of ML Test Based Decoders for Perceptually Watermarked Images

Based on the generalized Gaussian pdf of DCT coefficients of images, Hernandez et al. propose the ML test applied watermark decoder. For images with watermarks shaped by the visibility thresholds of DCT coefficients and the luminance masking of human visual system, they conclude that the ML test with an appropriately chosen parameter associated with the pdf of DCT coefficients outperforms the correlation based decoder. In this paper, the parameter is estimated using various methods including a novel one for watermarks shaped by the visibility thresholds of DCT coefficients and the luminance masking as Hernandez et al. did and with the contrast masking added, and its effect on performance is compared.