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Robust image watermarking based on multiwavelet parent-child relation and adaptive support vector regression

机译:基于多小波亲子关系和自适应支持向量回归的鲁棒图像水印

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In this paper, a robust image watermarking algorithm in multiwavelet domain is proposed. Multiwavelet transform provides good energy compaction and trade off between imperceptibility and watermark robustness properly. In the proposed algorithm, after performing a three-level multiwavelet decomposition, a parent-child relationship is defined between coefficients in different subbands. To increase the robustness, the relationship between the root node and its offspring nodes is learnt by support vector regression (SVR) and then the watermark is embedded and extracted based on this inherent relation. The good energy compaction property of multiwavelet can cause small number of coefficients containing most of image energy, therefore the range of target output values of SVR is extended which notably made inaccuracy in predictions. In order to overcome this problem, we proposed a procedure, which applies the inputs to SVR in an adaptive way. The experimental results show, the proposed algorithm possesses acceptable perceptual quality, while it is robust against common attacks such as JPEG, low-pass filtering, noise addition, cropping and resizing, etc.
机译:提出了一种鲁棒的多小波域图像水印算法。多小波变换提供了良好的能量压缩,并在不可感知性和水印鲁棒性之间做出了适当的权衡。在提出的算法中,在执行三级多小波分解之后,在不同子带中的系数之间定义了父子关系。为了提高鲁棒性,通过支持向量回归(SVR)学习根节点及其后代节点之间的关系,然后基于此固有关系嵌入并提取水印。多小波的良好的能量压缩特性会导致包含大部分图像能量的系数变少,因此SVR的目标输出值范围扩大了,这在预测中尤其不准确。为了克服这个问题,我们提出了一种程序,该程序以自适应方式将输入应用于SVR。实验结果表明,该算法具有良好的感知质量,对JPEG,低通滤波,噪声添加,裁剪和调整大小等常见攻击具有鲁棒性。

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