Open AccessSteganographic optical image encryption based on single-pixel imaging and an untrained neural network
Author(s) -
Shanshan Lin,
Xiaogang Wang,
Angang Zhu,
Jidong Xue,
xu bj
Publication year - 2022
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.467708
Subject(s) - encryption , computer science , steganography , pixel , artificial intelligence , computer vision , artificial neural network , information hiding , binary data , image quality , image (mathematics) , image processing , binary number , computer network , mathematics , arithmetic
We propose a steganographic optical image encryption based on single-pixel imaging (SPI) and an untrained neural network. In this encryption scheme, random binary illumination patterns are projected onto a secret image and light intensities reflected from the image are then detected by a bucket detector (BD). To enhance the security of collected secret data, a steganographic approach is introduced in this method, which implements data hiding with a SPI system using encoded illumination patterns. A non-secret image is illuminated with a sequence of encoded patterns that were generated from the scrambled measurements of secret image, and sequential cyphertext data can be obtained by collecting the diffraction data with the BD. Different from traditional SPI-based encryption schemes, an untrained neural network is adopted as a SPI-encrypted image processor, which allows to reduce time spent on data preparation and reconstruct the secret images with high quality. Both computer simulations and optical experiments are carried out to demonstrate the feasibility of the method.