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

机译:一种基于粒子群优化和CONTOUT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关键技术,数字水印通常会在难以忍受和稳健性之间看到困境。鉴于此问题,本文提出了一种基于CT-SVD的智能水印方案,包括三种主要算法,包括水印预处理,水印嵌入和提取。主机图像首先通过Contourlet变换分解,以获得在嵌入预处理的水印之前,然后在其上实现SVD分解的低频子带图像。水印提取是水印嵌入的反转。为了使水印稳健性最大化,同时保持其难以察觉的难以察觉,粒子群优化(PSO)被应用于具有缩放因子的启发式搜索。实验表明,该方案能够抵抗频繁的图像攻击,具有更好的不可察觉和鲁棒性。

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