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A review of single and multiple optical image encryption techniques
Journal of Optics ( IF 2.0 ) Pub Date : 2021-10-12 , DOI: 10.1088/2040-8986/ac2463
Abdurrahman Hazer , Remzi Yıldırım

Secure communication is of great importance in the modern world. Many methods, techniques, and systems are used for secure communication, many of which cannot be used in applications due to various reasons. Optical methods have been developed for secure communication in the last 25 years. In this study, optical encryption methods are examined in three sections. In the first section, single image optical encryption techniques are analyzed, while in the second section, multiple-image optical encryption techniques are examined. In the last section, standard test techniques for security are examined. The main single image optical encryption techniques are double random phase encoding (DRPE), DRPE and photon counting, phase truncated Fourier transform-based asymmetric optical encryption, diffractive imaging-based optical encryption, interference-based image encryption, and ghost imaging-based optical encryption. The main techniques of multiple-image optical encryption are wavelength multiplexing-based multiple-image encryption, position multiplexing-based multiple-image encryption, phase retrieval-based multiple-image encryption, 4-f correlation-based image encryption, and compressive sensing-based multiple-image encryption. These methods have been analyzed in detail and their advantages, disadvantages, and MATLAB application codes are given in the appendices.



中文翻译:

单、多光学图像加密技术综述

安全通信在现代世界中非常重要。许多方法、技术和系统用于安全通信,其中许多由于各种原因不能用于应用中。在过去的 25 年中,已经开发出用于安全通信的光学方法。在这项研究中,光学加密方法分为三个部分进行了检查。第一部分分析单图像光学加密技术,第二部分研究多图像光学加密技术。在最后一节中,检查了安全性的标准测试技术。主要的单图像光学加密技术有双随机相位编码(DRPE)、DRPE和光子计数、基于相位截断傅立叶变换的非对称光学加密、基于衍射成像的光学加密、基于干涉的图像加密和基于鬼成像的光学加密。多图像光学加密的主要技术有基于波长复用的多图像加密、基于位置复用的多图像加密、基于相位检索的多图像加密、基于4-f相关的图像加密和压缩感知-基于多图像加密。对这些方法进行了详细分析,并在附录中给出了它们的优缺点和MATLAB应用代码。和基于压缩感知的多图像加密。对这些方法进行了详细分析,并在附录中给出了它们的优缺点和MATLAB应用代码。和基于压缩感知的多图像加密。对这些方法进行了详细分析,并在附录中给出了它们的优缺点和MATLAB应用代码。

更新日期:2021-10-12
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