Image watermarking on degraded compressed sensing measurements

This paper proposes an additive watermarking on sparse or compressible coefficients of the host image in presence of blurring and additive noise degradation. The sparse coefficients are obtained through basis pursuit (BP). Watermark recovery is done through deblurring and performance is studied here for Wiener and fast total variation deconvolution (FTVD) techniques; the first one needs the actual or an estimate of the noise variance, while the second one is blind. Extensive simulations are done on images for different CS measurements along with wide range of noise variation. Simulation results show that FTVD with an optimum value for regularization parameter enables extraction of the watermark image in visually recognizable form, while Wiener deconvolution neither restores the watermarked image nor the watermark when no knowledge of noise is used.

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