结合遗传算法和独立分量分析优化图像隐写

F. Sadeghi, F. Kermani, M. Rafsanjani
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引用次数: 3

摘要

本文提出了一种将隐写术和密码学相结合的方法,将信息隐藏到数字图像中作为主机媒体。在此过程中,首先使用单字母替代密码方法对秘密数据进行加密,然后使用基于空间填充曲线(SFC)的随机模式和最优成对LSB匹配方法相结合的算法将加密后的秘密数据嵌入到图像中。本文采用遗传算法操作改进的帝国主义竞争算法,即离散帝国主义竞争算法(DICA),执行最优两两LSB匹配方法,并找到次优调整表。将该方法与其他方法在峰值信噪比方面的性能进行了比较。该方法的PSNR值比目前最先进的方法高出近4至5dB。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimizing image steganography by combining the GA and ICA
In this study, a novel approach which uses combination of steganography and cryptography for hiding information into digital images as host media is proposed. In the process, secret data is first encrypted using the mono-alphabetic substitution cipher method and then the encrypted secret data is embedded inside an image using an algorithm which combines the random patterns based on Space Filling Curves (SFC) and the optimal pair-wise LSB matching method. We employ a modified Imperialist Competitive Algorithm by Genetic Algorithm operations, namely Discrete Imperialist Competitive Algorithm (DICA), to perform the optimal pair-wise LSB matching method and find the suboptimum adjustment list. The performance of the proposed method is compared with other methods with respect to Peak Signal to Noise Ratio (PSNR). The PSNR value of the proposed method is higher than the state-of-the-art methods by almost 4dB to 5dB.
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