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Robust BlindWatermarking Algorithm Based on Contourlet Transform with Singular Value Decomposition

机译:基于奇异值分解的Contourlet变换的强大盲目算法

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In this Letter, we propose a blind and robust multiple watermarking scheme using Contourlet transform and singular value decomposition (SVD). The host image is first decomposed by Contourlet transform. Singular values of Contourlet coefficient blocks are adopted to embed watermark information, and a fast calculation method is proposed to avoid the heavy computation of SVD. The watermark is embedded in both low and high frequency Contourlet coefficients to increase the robustness against various attacks. Moreover, the proposed scheme intrinsically exploits the characteristics of human visual system and thus can ensure the invisibility of the watermark. Simulation results show that the proposed scheme outperforms other related methods in terms of both robustness and execution time.
机译:在这封信中,我们使用Contourlet变换和奇异值分解(SVD)提出了一种盲和强大的多水印方案。主机图像首先通过Contourlet变换分解。采用Contourlet系数块的奇异值来嵌入水印信息,并提出了一种快速的计算方法来避免SVD的重量计算。水印嵌入在低频和高频Contourlet系数中,以增加针对各种攻击的鲁棒性。此外,所提出的方案本质上利用人类视觉系统的特征,因此可以确保水印的隐形。仿真结果表明,该方案在鲁棒性和执行时间方面优于其他相关方法。

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