Open AccessInverse computational ghost imaging for image encryption
Author(s) -
Peixia Zheng,
Qilong Tan,
HongChao Liu
Publication year - 2021
Publication title -
optics express
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.428036
Subject(s) - encryption , ghost imaging , computer science , computational complexity theory , inverse , inverse problem , image quality , algorithm , process (computing) , theoretical computer science , image (mathematics) , computer vision , artificial intelligence , mathematics , computer security , mathematical analysis , geometry , operating system
Computer-generated random patterns and bucket detection are two key characteristics of computational ghost imaging (GI), which offer it a potential application in optical encryption. Here, we propose an inverse computational GI scheme, in which bucket signals are firstly selected and then random patterns are calculated correspondingly. Different GI reconstruction algorithms are used to test the inverse computational GI, and the relationship between imaging quality and error ratio factor is discussed as well. Compared with computational GI, our inverse one not only has disguised bucket signals but also provides an opportunity to combine with other cryptographies, both of which enrich the GI-based encryption process and enhance the security simultaneously.