Zheng Peixia, Ye Zhiyuan, Xiong Jun, Liu Hong-Chao
Opt Express. 2022 Jun 6;30(12):21866-21875. doi: 10.1364/OE.455975.
The principle of computational ghost imaging (GI) offers a potential application in optical encryption. Nevertheless, large numbers of keys composed of random or specific patterns set an obstacle to its application. Here, we propose a series of pattern compression methods based on computational GI, in which thousands of patterns are replaced by a single standard image (i.e., two-dimensional data), a sequence of numbers (i.e., one-dimensional data) or the fractional part of an irrational number (i.e., zero-dimensional data). Different pattern compression methods are tested in both simulations and experiments, and their error tolerances in encryption are further discussed. Our proposed methods can greatly reduce the pattern amount and enhance encryption security, which pushes forward the application of computational GI, especially in optical encryption.
计算鬼成像（GI）原理在光学加密领域具有潜在应用价值。然而，由随机或特定图案组成的大量密钥成为其应用的障碍。在此，我们提出了一系列基于计算鬼成像的图案压缩方法，其中数千个图案可被单个标准图像（即二维数据）、数字序列（即一维数据）或无理数的小数部分（即零维数据）所替代。在模拟和实验中对不同的图案压缩方法进行了测试，并进一步讨论了它们在加密中的容错能力。我们提出的方法能够大幅减少图案数量并增强加密安全性，推动了计算鬼成像的应用，尤其是在光学加密方面。
