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A Digital Watermarking Method Based on Particle Swarm Optimization and Contourlet Transform

机译:基于粒子群优化和Contourlet变换的数字水印方法

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As a key technology for digital content copyright protection, digital watermark often sees a dilemma between imperceptibility and robustness. In view of the problem, this paper suggests a CT-SVD-based intelligent watermarking scheme that embraces three major algorithms including the watermark preprocessing, the watermark embedding, and extracting. The host image is first decomposed by contourlet transform to get the low frequency subband images on which the SVD decomposition is then implemented before embedding the preprocessed watermark. The watermark extracting is an inversion of watermark embedding. To maximize the watermark robustness while maintaining its imperceptibility, particle swarm optimization (PSO) is applied to have heuristic searches for scaling factor. The experiment has demonstrated that this scheme is capable of resisting frequent image attacks with better imperceptibility and robustness.
机译:作为数字内容版权保护的一项关键技术,数字水印经常会在不可感知性和鲁棒性之间遇到两难选择。针对这一问题,本文提出了一种基于CT-SVD的智能水印方案,该方案包括水印预处理,水印嵌入和提取三大算法。首先通过轮廓波变换对宿主图像进行分解,以获得低频子带图像,然后在嵌入预处理水印之前对其进行SVD​​分解。水印提取是水印嵌入的反转。为了在保持水印不易察觉性的同时最大化水印的鲁棒性,应用了粒子群优化(PSO)进行启发式搜索缩放因子。实验表明,该方案能够抵抗频繁的图像攻击,并具有更好的不易察觉性和鲁棒性。

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