An efficient image system-based grey wolf optimiser method for multimedia image security using reduced entropy-based 3D chaotic map

Srinivas Koppu, V. M. Viswanatham
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Abstract

Chaotic maps play an important role in information sharing. In this paper a grey wolf optimiser used with reduced entropy-based 3D chaotic map. The selection and high coefficients are selected based on the reduced entropy value to identify the optimised parameters to get unpredictable random values. Time complexity, autocorrelation of V, H and D elements, histogram of original and cipher images, peak signal to noise ratio and NPCR and UACI values are computed from the cipher image. The empirical results show the proposed method provides good, better imperceptibility and defends various attacks. To prove this accomplishment of the method, several experiments were conducted and compared the results with existing systems.
一种有效的基于图像系统的灰狼优化方法,利用基于约熵的三维混沌映射实现多媒体图像安全
混沌映射在信息共享中起着重要的作用。本文提出了一种基于降熵的三维混沌映射的灰狼优化算法。根据约简熵值选择选择系数和高系数,识别最优参数,得到不可预测的随机值。从密码图像中计算时间复杂度、V、H、D元素的自相关、原始图像和密码图像的直方图、峰值信噪比、NPCR和UACI值。实验结果表明,该方法具有良好的隐蔽性和防御各种攻击的能力。为了证明该方法的有效性,进行了多次实验,并将实验结果与现有系统进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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