图像隐写的增强鲸鱼优化算法和小波变换

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引用次数: 21

摘要

在交互式环境中,信息安全被认为是信息技术发展的主要问题。在这种情况下,对发送到接收方或从接收方发送的消息没有任何保护。采用图像隐写技术,保证了隐写通信的安全性和信息的保护。在一些接收图像中,图像隐写术隐藏了秘密信息并传输了秘密信息,使得信息只有发送方和接收方可以看到。因此,本文提出了一种利用稀疏表示的图像隐写算法,并提出了一种称为增强鲸鱼优化算法(WOA)的方法,以有效地选择像素,从而将秘密音频信号嵌入到图像中。增强的基于WOA的像素选择过程利用了一个基于代价函数的适应度函数。为了评估适应度,代价函数计算熵、边缘和像素强度。实验结果表明,该算法与传统算法在PSNR和MSE方面进行了比较。进一步证明了所提出的增强WOA算法是一种有效的算法。为了解决上述问题,在SIS模型的基础上开发了一种(k, n)阈值部分可逆绝对矩块截断编码(AMBTC),并进行了身份验证和隐写。利用GF(28)中SIS的基础上的多项式,将秘密图像划分为n个类似噪声的份额。利用所提出的嵌入方法,利用奇偶校验位将它们隐藏到AMBTC封面图像中,并对n个有意义的隐进图像进行建模,以有效地处理这些共享。采用鉴权方法,验证了隐写图像的可靠性。足够的隐写图像可以完全重建秘密。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhanced Whale Optimization Algorithm and Wavelet Transform for Image Steganography
: In the interactive environment, information security is considered as the main issue with the development of information technology. Here, there is no protection for the messages transmitted to and from the receiver. A method called image steganography is used, which assures security to the concealed communication and protection of the information. In some of the receiver images, image steganography conceals the secret message and transmits the secret message so that the message is noticeable only to the transmitter and the receiver. Hence, this paper presents an algorithm for image steganography by exploiting sparse representation, and a method called Enhanced Whale Optimization Algorithm (WOA) in order to effectual selection of the pixels in order to embed the secret audio signal in the image. Enhanced WOA based pixel chosen process exploits a fitness function that is on the basis of the cost function. In order to evaluate the fitness, cost function computes the entropy, edge, and pixel intensity. Experimentation has been performed and a comparison of the proposed algorithm with the conventional algorithms regarding the PSNR and MSE. Moreover, it decides the proposed Enhanced WOA, as an effectual algorithm. to resolve the aforesaid issues, a (k, n) threshold partial reversible Absolute Moment Block Truncation Coding (AMBTC) on the basis of the SIS model with authentication and steganography was developed. Using the polynomial on the basis of the SIS in GF (28), a secret image was partition into n noise-similar to shares. They were hidden into the AMBTC cover image with parity bits using the developed embedding methods, and n meaningful stego images were modeled in order to competently deal with the shares. Authentication was used as a result that the reliability of stego image was confirmed. Adequate stego images can completely restructure the secret.
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