Perceptual watermarking using a new Just-Noticeable-Difference model

• We propose two perceptual models for watermarking.
• Both models are designed in the pyramid transform domain.
• The visibility model is proposed to embed the watermark into “invisible” regions.
• The JND model is to determine the visual detection threshold for the embedding strength.

In this paper, a new watermarking scheme based on Human Visual System (HVS) modeling is proposed. The approach consists in building computational models which take into account the most common properties of the HVS that can be exploited for watermarking. Two schemes for embedding and controlling the transparency of the watermark are presented, namely the implicit and the explicit schemes. Both schemes are designed in the framework of the pyramidal decomposition which has been shown to be a powerful tool for analyzing image through a multi-scale representation. For the first approach, a multi-scale visibility map is used to optimize the watermark embedding process. The second approach makes use of HVS properties in an explicit and more sophisticated manner that consists in tuning the watermark strength just beneath the visual detection threshold. A new JND (Just-Noticeable-Difference) model for determining this threshold is then proposed and evaluated. The obtained results provide a strong support for this new JND model.