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Image steganography based on sparse decomposition in wavelet space

机译:小波空间中基于稀疏分解的图像隐写术

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Sparse decomposition of wavelet coefficients of cover image blocks for data hiding is addressed in this paper. By using the proposed algorithm, the embedded secret message can be reliably extracted without resorting to the original image. We use all four sub-images (LL, LH, HL and HH) of the 2D wavelet transform for data embedding without losing the image imperceptibility. An over-complete dictionary matrix is estimated by using the KSVD dictionary learning algorithm, and then the secret message bits are inserted in the sparse representation of the wavelet coefficients over the estimated dictionary. This is believed to be one of the first approaches to the image data hiding that uses the sparse decomposition. Our experimental results show that the proposed method is robust against cropping and noise addition attacks. It is also robust against the lower than 0.2 degree rotation attacks. The results also show it possesses resistance to high order statistics analysis.
机译:本文研究了用于图像隐藏的封面图像块小波系数的稀疏分解。通过使用所提出的算法,可以在不依靠原始图像的情况下可靠地提取嵌入的秘密消息。我们使用二维小波变换的所有四个子图像(LL,LH,HL和HH)进行数据嵌入,而不会丢失图像的不可感知性。通过使用KSVD字典学习算法来估计不完整的字典矩阵,然后将秘密消息位插入到估计字典中的小波系数的稀疏表示中。据信这是使用稀疏分解的图像数据隐藏的第一种方法。我们的实验结果表明,所提出的方法对裁剪和噪声添加攻击具有鲁棒性。对于低于0.2度的旋转攻击,它也很强大。结果还表明它具有抗高阶统计分析的能力。

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