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A Multiple-Level DCT Based Robust DWT-SVD Watermark Method

机译:基于多级DCT的鲁棒DWT-SVD水印方法

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The contradiction between the capacity and the robustness of image watermark has not been solved in the digital watermark research. In this paper, a robust Discrete Wavelet Transform (DWT) - Singular Value Decomposition (SVD) watermark method based on multiple-level Discrete Cosine Transform (DCT) is proposed by the advantage of DCT's energy concentration. Firstly, the carrier image is done discrete wavelet transform and its low frequency sub-band is obtained. Secondly, the coefficient matrix of the low frequency sub-band is partitioned. Then each block is done multiple-level DCT. Thirdly, according to the capacity of the embedded watermark, the appropriate DCT coefficients are selected in each block to form a new matrix, and then the encrypted watermark is embedded in the singular value matrix of the new matrix. Finally, the image containing watermark is obtained by SVD synthesis, multiple-level inverse DCT and multiple-level inverse DWT. Experimental results show that compared with other similar watermark methods, this paper's method not just can embed the large-capacity watermark by dynamically selecting the appropriate DCT coefficients, but also has robustness to different image attacks.
机译:数字水印研究尚未解决图像水印的容量与鲁棒性之间的矛盾。本文利用DCT的能量集中度,提出了一种基于多级离散余弦变换(DCT)的鲁棒离散小波变换(DWT)-奇异值分解(SVD)水印方法。首先,对载波图像进行离散小波变换,得到其低频子带。其次,对低频子带的系数矩阵进行划分。然后,每个块都完成多级DCT。第三,根据嵌入的水印的容量,在每个块中选择适当的DCT系数以形成新的矩阵,然后将加密的水印嵌入到新矩阵的奇异值矩阵中。最后,通过SVD合成,多级逆DCT和多级逆DWT获得了包含水印的图像。实验结果表明,与其他类似的水印方法相比,该方法不仅可以通过动态选择合适的DCT系数来嵌入大容量水印,而且对不同的图像攻击具有鲁棒性。

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