Robust watermarking of Compressive Sensed signals

In this work, we propose a watermark algorithm that embeds information directly onto Compressive Sensed Measurements of a sparse signal. Proposed watermarking algorithm outperforms the classical ℓ₂ and ℓ₁ minimization algorithms in terms of watermark embedding capacity. Experimental results show that the proposed algorithm has a robust reconstruction performance under Gaussian and impulsive noise.