Robust Watermarking in DoG Scale Space Using a Multi-scale JND Model
PCM '09 Proceedings of the 10th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
A new spatio-temporal JND model based on 3D pyramid decomposition
PCM'10 Proceedings of the Advances in multimedia information processing, and 11th Pacific Rim conference on Multimedia: Part II
Perceptual watermarking using a multi-scale JNC model
ACIIDS'10 Proceedings of the Second international conference on Intelligent information and database systems: Part II
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A new pyramidal JND (Just Noticeable Difference) model is presented. The idea is to use this JND to determine the optimum strength for embedding the watermark providing an invisible and robust watermarking scheme. The image is first decomposed into a multiresolution representation using the pyramidal decomposition. Then, a perceptual model is proposed to compute the JND value for each pixel at each Laplacian level. This model takes into account three main characteristics of the Human Visual System (HVS), namely: contrast sensitivity, luminance adaptation and contrast masking. The performance of the proposed technique is evaluated in terms of transparency, using subjective and objective tests, and robustness to different common attacks.