A self-adaptive image normalization and quaternion PCA based color image watermarking algorithm
A self-adaptive image normalization and quaternion PCA based color image watermarking algorithm
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一种基于自适应图像归一化和四元数PCA的彩色图像水印算法
DOI：
10.1016/j.eswa.2012.03.070
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发表时间：
2012-11
影响因子：
8.5
通讯作者：
郎方年
中科院分区：
文献类型：
--
作者：
郎方年
提出了一种新的鲁棒彩色数字水印算法，该算法结合了彩色图像特征点提取、形状图像归一化和基于四元数主成分算法（QPCA）的水印嵌入和提取方案。该算法采用Mexican Hat小波尺度交互作用的特征点提取方法来选择能够抵抗各种攻击的特征点，并将其作为水印嵌入和提取的参考点。以四个角点为原始图像特征点的局部四边形图像的归一化形状图像具有平移、旋转、缩放和倾斜不变性，通过该图像的归一化形状图像可以得到原始图像和受几何攻击的水印图像的特征图像之间的关系。所提出的QWEMS和QWEXS方案将彩色像素表示为纯四元数，将特征图像表示为四元数矩阵，可以提高水印嵌入的鲁棒性和不可感知性。为了简化四元数矩阵的特征分解过程，提出了一种计算四元数矩阵的特征值和特征向量的方法。在特征图像的主成分系数中嵌入二值水印图像。仿真结果表明，该算法能够抵抗平移、旋转、缩放、倾斜等几何攻击，也能够抵抗JPEG压缩、椒盐噪声、高斯滤波、中值滤波等多种信号处理过程的攻击。
This paper proposes a novel robust digital color image watermarking algorithm which combines color image feature point extraction, shape image normalization and QPCA (quaternion principal component algorithm) based watermarking embedding (QWEMS) and extraction (QWEXS) schemes. The feature point extraction method called Mexican Hat wavelet scale interaction is used to select the points which can survive various attacks and also be used as reference points for both watermarking embedding and extraction. The normalization shape image of the local quadrangle image of which the four corners are feature points of the original image is invariant to translation, rotation, scaling and skew, by which we can obtain the relationship between the feature images of the original image and the watermarked image which has suffered with geometrical attacks. The proposed QWEMS and QWEXS schemes which denote the color pixel as a pure quaternion and the feature image as a quaternion matrix can improve the robustness and the imperceptibility of the embedding watermarking. To simplify the eigen-decomposition procedure of the quaternion matrix, we develop a calculation approach with which the eigen-values and the corresponding eigen-vectors of the quaternion matrix can be computed. A binary watermark image is embedded in the principal component coefficients of the feature image. Simulation results demonstrate that the proposed algorithm can survive a variety of geometry attacks, i.e. translation, rotation, scaling and skew, and can also resist the attacks of many signal processing procedures, for example, moderate JPEG compression, salt and pepper noise, Gaussian filtering, median filtering, and so on.
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DOI：
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发表时间：
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期刊：
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影响因子：
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DOI：
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发表时间：
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期刊：
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DOI：
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期刊：
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影响因子：
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DOI：
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发表时间：
1989-10
期刊：
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影响因子：
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DOI：
10.1016/j.eswa.2017.04.021
发表时间：
2017-10
期刊：
Expert Syst. Appl.
影响因子：
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Lei Zhang;D. Zhang;Ming-ming Sun;Fangmei Chen