A spatiotemporal saliency-modulated JND profile applied to video watermarking

The just noticeable distortion (JND) has been considered a suitable solution for controlling the watermark strength and generating robust watermarking schemes with distortions that are below the sensitivity threshold. However, JND assumes the same attention level for all image regions, which does not reflect the behavior of an observer. Recently, several models have utilized the modulatory effect of visual attention over JND to improve the efficiency of watermarking schemes. However, most of them have focused on still images. In this paper, we propose a saliency-modulated JND profile for improving video watermarking schemes. Our method aims to adapt the watermark strength to obtain the most robust possible scheme with an imperceptible watermark. Moreover, it has the advantage of fully exploiting the spatiotemporal properties of video to minimize its perceptual redundancies and achieve low computational complexity. Experimental results show the effectiveness of our proposed method and its contributions to video watermarking process.