基于奇异值分解和神经网络的鲁棒图像水印混合方法

Mokhtar Hussein, B.Man jula
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引用次数: 0

摘要

在数字世界中,人们提出了许多用于多媒体数据版权保护的数字水印技术,以避免其误用。这些水印方案的实现主要关注鲁棒性、可信度和不可感知性。提出了一种新的基于奇异值分解和神经网络的鲁棒图像水印方法。该方法对不同类型的攻击和复制移动伪造攻击具有更好的图像质量和鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Hybrid Approach for SVD and Neural Networks Based Robust Image Watermarking
In the digital world, a lot of digital watermarking techniques for copyright protection of multimedia data have been proposed to avoid their misuse. Implementation of these watermarking schemes requires main focus on robustness, trustworthiness and imperceptibility. In this paper, a new SVD and Neural Network based robust image watermarking method is proposed. The proposed method is supposed to offer better quality and robustness for the image under different types of attacks and under copy move forgery attacks.
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