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The present paper proposes a discrete cosine transform (DCT) domain watermarking scheme by exploiting nonlinear dynamical saturating detectors in the design of a watermark detection process. A binary copyright character, i.e. watermark to be hidden into an image, is firstly reordered into a binary zig-zag sequence, and then mapped onto the pulse amplitude modulated signal. A certain desynchronization time delay can be deliberately placed into one code of the modulated signal, and is tolerated due to the superior robustness of nonlinear detectors over matched filters. A selected set of DCT coefficients of a host image in a mid frequency range is shuffled by the Arnold transform, which makes it look more like background noise with respect to the watermark signal. Then, the watermark signal is embedded in the set of shuffled DCT coefficients. The copyright character can be extracted by a nonlinear saturating detector without prior knowledge of the original image and watermark, i.e. blind watermark detection. Interestingly, a higher match between the original watermark character and the extracted one can be further achieved by a parallel array of nonlinear detectors via the mechanism of array stochastic resonance. Robustness of the proposed watermarking scheme is shown in the presence of noise, filtering, cropping, and compression.

Reordering by the rule of decreased absolute amplitudes, the discrete cosine transformation (DCT) coefficients of an image are approximately modeled as dichotomous noise. Based on this assumption, it is interesting to note that the classical multiplicative embedding method can be transformed into an additive embedding rule, which accords with the signal processing problem of detecting a known weak signal in additive non-Gaussian noise. Then, following the generalized Neyman-Pearson lemma, a locally optimum detector, named the sign detector, is introduced to distinguish the correct watermark from the wrong ones. The statistical characteristics of this nonlinear sign detector are analytically investigated in detail. Extensive experimental results demonstrate the robustness of watermark against some common attacks, e.g., JPEG compression, cropping, filtering, additive Gaussian noise, dithering, and also verify the robust performance of the nonlinear sign detector for watermark detection.