基于压缩感知理论和混沌理论的彩色数字图像DCT-SVD域水印

Meng Li, Chao Han
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引用次数: 8

摘要

提出了一种基于压缩感知理论和混沌理论的离散余弦变换(DCT)和奇异值分解(SVD)域彩色图像水印算法。首先对彩色水印图像进行红、绿、蓝通道分割、小波变换稀疏、一维混沌序列置乱、高斯随机矩阵测量四步预处理。在这里,混沌序列是由一维Logistic映射产生的。然后将彩色主机图像的红、绿、蓝通道图像分成8×8块,再进行DCT变换。然后选取每个块的第一个DCT系数组成一个新矩阵,并对新矩阵进行奇异值分解。奇异值是水印嵌入的区域。第三,将三组实测系数作为新的水印嵌入到对应的奇异值中;最后,采用迭代硬阈值(IHT)算法对水印图像进行重构。该方法在具有良好的不可感知性的情况下,不仅可以扩大水印嵌入的信息容量,而且可以增强水印的安全性。实验表明,该方案是可行的,对JPEG压缩、高斯白噪声、旋转滤波和中值滤波具有良好的抗攻击能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A DCT-SVD Domain Watermarking for Color Digital Image Based on Compressed Sensing Theory and Chaos Theory
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.
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