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A novel robust watermarking scheme based on neural network

机译:一种基于神经网络的鲁棒水印新方案

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A color image oblivious watermarking scheme based on neural network and discrete wavelet transform (DWT) is proposed in this paper. Three identical watermarks and some different expanded bit streams are adaptively embedded into the low frequency sub-bands generated from three channels for a color image, respectively. Due to the adaptive learning capabilities of neural network, the expanded bit streams could be used to train back propagation (BP) neural networks to represent the relationship among the neighbor wavelet coefficients. Based on the trained neural networks, three watermarking results can be extracted and then are voted to decide the final watermark. Extensive experiments illustrate that the new scheme possesses good robustness against different attacks including noise addition, shearing, scaling, luminance and distortion. And what's more, the scheme has excellent performance in term of imperceptibility and resistance to JPEG compression.
机译:提出了一种基于神经网络和离散小波变换(DWT)的彩色图像无水印方案。将三个相同的水印和一些不同的扩展位流分别自适应地嵌入到从三个通道生成的彩色图像的低频子带中。由于神经网络的自适应学习能力,扩展的比特流可用于训练反向传播(BP)神经网络,以表示相邻小波系数之间的关系。基于训练后的神经网络,可以提取三个水印结果,然后将其投票决定最终的水印。大量实验表明,该新方案对包括噪声添加,剪切,缩放,亮度和失真在内的各种攻击具有良好的鲁棒性。而且,该方案在不易察觉和抗JPEG压缩方面具有出色的性能。

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