结合变换及其混合小波的遗传算法在提高图像隐写性能中的作用

Shweta Joshi, Kavita Sonawane, S. Khan
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引用次数: 2

摘要

提出了一种隐藏秘密图像的图像隐写算法。提出的工作目标是在保证图像安全性的同时增加嵌入容量。使用两个级别的处理来解决这个问题。首先是将遗传算法(GA)作为“嵌入前隐藏技术”的应用,它试图在掩蔽图像中识别出嵌入秘密图像不会导致图像失真的合适位置。第二步是利用离散余弦变换(DCT)及其小波变换(DCWT)进行改进,以获得其能量压缩特性的优势。所述秘密图像嵌入在覆盖图像的较低能量变换区域中。本文对使用遗传算法和不使用遗传算法的DCT和DCWT进行了比较。利用均方误差(MSE)、峰值信噪比(PSNR)和相关性等性能评价参数对实验结果进行评价。综合比较表明,DCT和DCWT与遗传算法相结合的效果更好。实验还证明了所提出的两级处理方法不仅提高了图像隐写的安全性,而且提高了嵌入容量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Role of genetic algorithm in performance improvement of image steganography combined with transform and its hybrid wavelet
This paper proposes an image steganography for hiding secret images. The objective of the proposed work is to increase the embedding capacity while ensuring the security of the image. This has been addressed using two levels of processing. First is the application of Genetic Algorithm (GA) as ‘before embedding hiding technique’ which tries to identify suitable places in cover image where embedding of secret image will not lead to much distortion in the image. Second process is improvement using Discrete Cosine Transform (DCT) and its wavelet (DCWT) to gain the advantage of their energy compaction property. The secret image is embedded in the lower energy transformed regions of the cover image. The paper makes a comparison between DCT and DCWT (with and without using GA). The experimental results are evaluated using various performance evaluation parameters such as Mean Square Error (MSE), Peak Signal-to-Noise Ratio (PSNR) and Correlation. The overall comparison proves that both DCT and DCWT perform better when combined with genetic algorithm. This work also proves that the proposed two level processing contributes in improvement of both security as well as embedding capacity for the image steganography.
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