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Blind Watermark Algorithm Based on HVS and RBF Neural Network in DWT Domain

机译:DWT域中基于HVS和RBF神经网络的盲水印算法

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摘要

This paper proposes a new blind watermarking scheme based on discrete wavelet transform(DWT) domain. The method uses the HVS model, and radial basis function neural networks(RBF). RBF will be implemented while embedding and extracting watermark. The human visual system (HVS) model is used to determine the watermark insertion strength. The neural networks almost exactly recover the watermarking signals from the watermarked images after training and learning. The experimental results show that the watermark proposed in this paper is invisible (the PSNR is higher than 41) and is robust in the case of against some normal at tacks such as JPEG compression, additive noise and filtering, etc.
机译:提出了一种基于离散小波变换(DWT)域的盲水印方案。该方法使用HVS模型和径向基函数神经网络(RBF)。 RBF将在嵌入和提取水印时实施。人类视觉系统(HVS)模型用于确定水印插入强度。在训练和学习之后,神经网络几乎可以从水印图像中准确地恢复出水印信号。实验结果表明,本文提出的水印是不可见的(PSNR高于41),并且在针对某些正常情况(如JPEG压缩,加性噪声和滤波等)时具有鲁棒性。

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