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A DCT-SVD Domain Watermarking for Color Digital Image Based on Compressed Sensing Theory and Chaos Theory

机译:基于压缩感知和混沌理论的彩色数字图像DCT-SVD域水印

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In this paper, it is presented that a new color image watermarking algorithm based on compressed sensing theory and chaos theory in discrete cosine transform (DCT) and singular value decomposition (SVD) domain. Initially, a color watermarking image is preprocessed by four steps i.e. Being divided into red, green and blue channels, being sparse by wavelet transform, scrambling by 1-D chaos sequence and measurement through Gaussian random matrix. Here, the chaos sequence is produced by 1-D Logistic mapping. Then the red, green and blue channel images of a color host image are divided into 8×8 blocks and then transformed by DCT. Next the first DCT coefficient of each block is selected to compose a new matrix, and the new matrix is decomposed by SVD. The singular values are the regions of watermarking embedment. Thirdly, three sets of measured coefficients as new watermarking are embedded into the corresponding singular values. Finally, the Iterative Hard Threshold (IHT) algorithm is used to reconstruct the watermarking image. The method proposed can not only enlarge the information capacity of watermarking embedment but also strengthen the security of watermarking in the condition of the good imperceptibility. The experiments show that the scheme is feasible and has good anti-attack ability for JPEG compression, Gaussian white noise, rotating and median filtering.
机译:在离散余弦变换(DCT)和奇异值分解(SVD)域中,提出了一种基于压缩感知理论和混沌理论的彩色图像水印算法。最初,通过四个步骤对彩色水印图像进行预处理,即分为红色,绿色和蓝色通道,通过小波变换稀疏,通过一维混沌序列加扰,以及通过高斯随机矩阵进行测量。在这里,混沌序列是通过一维逻辑映射产生的。然后将彩色主机图像的红色,绿色和蓝色通道图像划分为8×8块,然后通过DCT进行转换。接下来,选择每个块的第一DCT系数以组成新矩阵,并且该新矩阵通过SVD分解。奇异值是水印嵌入的区域。第三,将三组测量系数作为新的水印嵌入到相应的奇异值中。最后,使用迭代硬阈值(IHT)算法重建水印图像。所提出的方法不仅可以扩大水印嵌入的信息容量,而且可以在不易察觉的情况下增强水印的安全性。实验表明,该方案可行,对JPEG压缩,高斯白噪声,旋转和中值滤波具有良好的抗攻击能力。

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