Perceptual Watermarking should take full advantage of the results from human visual system (HVS) studies. Just noticeable distortion (JND), which refers to the maximum distortion that the HVS does not perceive, gives a way to model the HVS accurately. An effective Spatio-Temporal JND model guided video watermarking scheme in DCT domain is proposed in this paper. The watermarking scheme is based on the design of an additional accurate JND visual model which incorporates spatial Contrast Sensitivity Function (CSF), temporal modulation factor, retinal velocity, luminance adaptation and contrast masking. The proposed watermarking scheme, where the JND model is fully used to determine scene-adaptive upper bounds on watermark insertion, allows providing the maximum strength transparent watermark. Experimental results confirm the improved performance of the Spatio-Temporal JND model. The authors’ Spatio-Temporal JND model is capable of yielding higher injected-watermark energy without introducing noticeable distortion to the original video sequences and outperforms the relevant existing visual models. Simulation results show that the proposed Spatio-Temporal JND model guided video watermarking scheme is more robust than other algorithms based on the relevant existing perceptual models while retaining the watermark transparency.
A Robust Video Watermarking Scheme with Squirrel Search Algorithm
