Spatio-temporal Just Noticeable Distortion Model Guided Video Watermarking

  • Authors:

  • Yaqing Niu;Jianbo Liu;Sridhar Krishnan;Qin Zhang

  • Affiliations:

  • Information Engineering School, Communication University of China, Beijing, China and Department of Electrical and Computer Engineering, Ryerson University, Toronto, Canada;Information Engineering School, Communication University of China, Beijing, China;Department of Electrical and Computer Engineering, Ryerson University, Toronto, Canada;Information Engineering School, Communication University of China, Beijing, China

  • Venue:
  • PCM '09 Proceedings of the 10th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
  • Year:
  • 2009

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Abstract

Perceptual video watermarking needs to take full advantage of the results from human visual system (HVS) studies. Since motion is a specific feature of video, temporal HVS properties need to be taken into account. In this paper, we exploit a combined Spatio-Temporal Just Noticeable Distortion (JND) model which incorporates spatial CSF, temporal modulation factor, retinal velocity, luminance adaptation and contrast masking to guide watermarking for digital video. The proposed watermarking scheme, where visual models representing additional accurate perceptual visibility threshold are fully used to determine scene-driven upper bounds on watermark insertion, allows us to provide the maximum strength transparent watermark. Experimental results confirm the improved performance of our combined Spatio-Temporal JND model guided watermarking scheme. Our Spatio-Temporal JND model guided watermarking scheme which allows higher injected-watermark energy without jeopardizing picture quality performs much better on robustness than other algorithms based on the relevant existing perceptual models.