基于整数小波变换和赋值算法的数字图像隐写

Neda Raftari, A. Eftekhari-Moghadam
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引用次数: 38

摘要

本文提出了一种基于整数小波变换和Munkres分配算法的图像隐写新技术,将秘密图像嵌入到覆盖图像的频域,具有较高的匹配质量。利用小波变换将覆盖图像和秘密图像从空域变换到频域,并利用分配算法实现块间的最佳匹配。我们将秘密图像嵌入到水平细节、垂直细节和对角细节等掩蔽图像的不同系数波段,观察嵌入对隐写图像峰值信噪比(PSNR)性能的影响。实验结果表明,隐写图像和提取的秘密图像具有较高的视觉质量,并且在感知上与原始图像相似。此外,该方法对六种不同的攻击具有较高的鲁棒性。嵌入对角细节系数比其他系数具有更好的信噪比。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Digital Image Steganography Based on Integer Wavelet Transform and Assignment Algorithm
In this paper, we present a new image steganography technique based on Integer Wavelet Transform (IWT) and Munkres' assignment algorithm which embeds secret image in frequency domain of cover image with high matching quality. IWT is used to transform both cover and secret images from spatial domain to frequency domain, and assignment algorithm is used for best matching between blocks for embedding. We embed the secret image in different coefficients of cover image bands such as horizontal detail, vertical detail and diagonal detail and observe the effect of embedding on the performance of stego image in terms of Peak Signal to Noise Ratio (PSNR). Experimental results depict that stego image and extracted secret image could have high visual quality and they are perceptually similar to their original versions. In addition, this method shows high robustness against six different attacks. Embedding in diagonal detail coefficients gives better PSNR than other coefficients.
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