Open AccessGhost identification based on single-pixel imaging in big data environment
Author(s) -
Wen Chen
Publication year - 2017
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.25.016509
Subject(s) - ghost imaging , pixel , computer science , perspective (graphical) , big data , artificial intelligence , detector , identification (biology) , computer vision , data mining , telecommunications , botany , biology
In recent years, single-pixel imaging has become one of the most interesting and promising imaging technologies for various applications. In this paper, a big data environment for the first time to my knowledge is designed and introduced into single-pixel ghost imaging for securing information. Many series of one-dimensional ciphertexts are recorded by a single-pixel bucket detector to form a big data environment. Several hidden inputs are further encoded based on ghost imaging by using hierarchical structure, and their corresponding ciphertexts are synthesized into the big data environment for verifying the hidden ghosts and identifying the targeted ghosts. This new finding could open up a different research perspective for exploring more applications based on single-pixel imaging.