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Effective Hill Climbing Algorithm for Optimality of Robust Watermarking in Digital Images

机译:用于数字图像鲁棒水印优化的有效爬山算法

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Due to the explosion of data sharing on the internet and the massive use of digital media, especially digital images, there is great interest by image owners in copyright protection . The genetic watermarking methods were previously shown to optimize the conflicting requirements of robustness and invisibility. However, the genetic watermarking methods have limitation in considering perceptually significant or non-significant regions in the selection process, so they do not always offer better imperceptibility. In addition, the computational resource required by Genetic Algorithm (GA) is high when comparing it to other heuristic methods. Thus, the current study is focused on an optimization-based Dither Modulation watermarking scheme for digital images in a more efficient and effective manner. The watermark imperceptibility and robustness are taken into consideration at the same time. A hill climbing algorithm, which has a simple computational process, is employed for optimizing these two conflicting requirements. Since, Peak Signal-to-Noise Ratio (PSNR) may not be an effective imperceptibility measure presented previous genetic watermarking methods, Watson?s perceptual model is employed to quantify the watermarked image distortion as it is consistent with Human Visual System (HVS). Several commonly used watermarking attacks are considered in the optimization process. Experimental results demonstrated that the proposed algorithm is robust and more time efficient than the previous GA based methods.
机译:由于互联网上数据共享的爆炸式增长以及数字媒体(尤其是数字图像)的大量使用,图像所有者对版权保护产生了极大的兴趣。遗传水印方法先前已被证明可以优化鲁棒性和隐形性的冲突要求。但是,遗传水印方法在选择过程中考虑到感知上重要或非重要区域方面存在局限性,因此它们并不总是提供更好的不可感知性。此外,与其他启发式方法进行比较时,遗传算法(GA)所需的计算资源很高。因此,当前的研究集中于以更优化和有效的方式基于优化的数字图像抖动调制水印方案。同时考虑水印的不可感知性和鲁棒性。采用具有简单计算过程的爬山算法来优化这两个相互矛盾的要求。由于峰值信噪比(PSNR)可能不是以前遗传水印方法提出的有效的不可感知性度量,因此使用Watson的感知模型来量化水印图像失真,因为它与人类视觉系统(HVS)一致。在优化过程中考虑了几种常用的水印攻击。实验结果表明,与基于遗传算法的算法相比,该算法具有较强的鲁棒性和时效性。

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