一种新的基于ct的基于位置尺度分布的乘性图像水印统计检测器

Sadegh Etemad, M. Amirmazlaghani
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引用次数: 2

摘要

本文提出了一种基于contourlet域的统计乘法水印检测方法。图像的轮廓线系数具有高度的非高斯性,用重尾概率分布函数来模拟轮廓线系数的统计量是合适的。在本研究中,提出了一种利用位置尺度分布(tLS)在contourlet域中进行乘法水印的方案。然后,我们利用似然比决策规则和tLS分布设计了一个最优的乘法水印检测器。实验结果表明,该检测器比文献中的其他水印方案效率更高,并验证了其对不同攻击的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A new statistical detector for CT-based multiplicative image watermarking using the t location-scale distribution
In this study, a new statistical multiplicative watermark detector in contourlet domain is presented. The contourlet coefficients of images are highly non-Gaussian and a proper distribution to model the statistics of the contourlet coefficients is a heavy-tail Probability Distribution Function (PDF). In this study, a multiplicative watermarking scheme is proposed in the contourlet domain using t location-scale distribution (tLS). Afterward, we used the likelihood ratio decision rule and tLS distribution to design an optimal multiplicative watermark detector. The detector showed higher efficiency than other watermarking schemes in the literature, based on the experimental results, and its robustness against different attacks was verified.
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