A Compressive Sensing Based Quantized Watermarking Scheme with Statistical Transparency Constraint

In multimedia protection processes, quantization based watermarking schemes are widely used. For these processes, the proposed watermarking solutions offer robust approaches for copyright protection. Unfortunately in key-less solutions, the additional hidden information (watermark) is, statistically detectable by unauthorized users, and thus they are correctly informed on the documents to be attacked or not. In this paper, we present a compressive sensing based watermarking solution able to mark digital pictures increasing statistical invisibility for attackers: the attacker will falsely conclude to a non-watermarked document with high probability. We discuss the way of using compressive sensing on the host signal for watermarking purpose. We describe a solution allowing to obtain a watermarking scheme based on compressive sensing with interesting properties for images protection processes. All the watermarking performances are discussed for three criteria robustness, statistical invisibility and capacity in order to look for the best trade-off. All the analysis are validated on digital image databases.