Image steganography Based on Chaos Permutation, Authentication and Wiener Deconvolution

A. Sheidaee, M. Asadpour, Leili Farzinvash
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Abstract

Image steganography refers to hiding a secret image into another meaningful one. Researchers have employed different algorithms such as wavelet transform, discrete cosine transform functions to transform secret image and different image processing algorithms like image encryption utilized to reach better stego images in case of imperceptibility and robustness. In most of researches, higher robustness methods have lower impeccability and vice versa. In this paper, we propose an adaptive LSB method using chaos permutation, DCT, and secret image authentication to increase both imperceptibility and robustness. Chaos permutation is a key feature in our work to improve the robustness of secret image against attacks and wiener filter deconvolution is employed to extract a clear secret image in receiver side, which has the lowest noise in comparison with the original secret image. The improvement of our proposed method have been analyzed and evaluated by different criteria such as PSNR, SSIM and Histogram plots.
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基于混沌置换、认证和维纳反卷积的图像隐写
图像隐写术是指将一个秘密图像隐藏到另一个有意义的图像中。研究者们采用了不同的算法,如小波变换、离散余弦变换函数对秘密图像进行变换,采用了不同的图像处理算法,如图像加密,以达到更好的隐化图像,同时又具有不可感知性和鲁棒性。在大多数研究中,鲁棒性越高的方法的无可挑剔性越低,反之亦然。在本文中,我们提出了一种自适应LSB方法,使用混沌置换、DCT和秘密图像认证来提高不可感知性和鲁棒性。混沌置换是提高秘密图像抗攻击鲁棒性的关键特征,并利用维纳滤波反卷积在接收端提取出清晰的秘密图像,与原始秘密图像相比,该图像具有最低的噪声。通过不同的标准,如PSNR、SSIM和直方图,分析和评价了我们提出的方法的改进。
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