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Image watermarking on degraded compressed sensing measurements

机译:降级压缩感知测量的图像水印

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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.
机译:本文提出了在存在模糊和加性噪声降级的情况下,对主机图像的稀疏或可压缩系数进行加性水印处理的方法。稀疏系数是通过基本追踪(BP)获得的。水印恢复是通过去模糊来完成的,在此我们研究了维纳和快速总变化反卷积(FTVD)技术的性能;第一个需要实际或估计噪声方差,而第二个则是盲目的。针对不同的CS测量以及广泛的噪声变化,在图像上进行了广泛的仿真。仿真结果表明,具有最佳正则化参数值的FTVD能够以视觉上可识别的形式提取水印图像,而在不使用噪声知识的情况下,维纳反卷积既不会恢复水印​​图像也不会恢复水印​​。

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