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首页> 外文期刊>Optik: Zeitschrift fur Licht- und Elektronenoptik: = Journal for Light-and Electronoptic >An improved robust image watermarking method using DCT and YCoCg-R color space
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An improved robust image watermarking method using DCT and YCoCg-R color space

机译:一种改进的鲁棒图像水印方法,使用DCT和Ycocg-R色空间

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摘要

Watermarking is one of the solutions to prevent unauthorized use of digital media. This solution can help the protection of ownership rights by embedding the copyright information in the intended media. In this paper, a digital image watermarking algorithm in YCoCg-R color space is proposed. Thriplet components of YCoCg-R color space have a good decorrelation and changing one component has the least impact on the two other color components. So it can be effective in increasing the robustness of watermarking against various attacks. For watermark embedding the proposed method uses Discrete Cosine Transform and its coefficients relationship. During watermark bits embedding, complexity amount of host image blocks is utilized to select the target blocks and energy value of host image blocks is used to adaptive selection of embedding strengths that it causes a very high robustness especially against JPEG compression. The Arnold transformation, also, plays an important role in increasing the security of our proposed method by scrambling the watermark. Considering the conflict among three main requirements of watermarking, including imperceptibility, robustness and capacity, the proposed method is compared with other algorithms and the results show the superior robustness of the proposed method over the other algorithms with same capacity. (c) 2017 Elsevier GmbH. All rights reserved.
机译:水印是防止未经授权使用数字媒体的解决方案之一。该解决方案可以通过在预期媒体中嵌入版权信息来帮助保护所有权权。本文提出了一种在YCOCG-R色空间中的数字图像水印算法。 Ycocg-R色空间的Thriplet组件具有良好的去相关性,并且改变一个部件对两个其他颜色组件的影响最小。因此,可以有效地增加水印对各种攻击的鲁棒性。对于嵌入的水印嵌入该方法使用离散余弦变换及其系数关系。在水印比特嵌入期间,使用主机图像块的复杂度量来选择主机图像块的目标块和能量值用于自适应选择它导致非常高的鲁棒性的嵌入强度,尤其是针对JPEG压缩。同时转型,也在提高水印中提高我们提出的方法的安全性的重要作用。考虑到水印的三个主要要求之间的冲突,包括难以察觉,鲁棒性和容量,将所提出的方法与其他算法进行比较,结果表明了所提出的方法在具有相同容量的其他算法上的优越稳健性。 (c)2017年Elsevier GmbH。版权所有。

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