Open AccessGerchberg-Saxton-like ghost imaging
Author(s) -
Wei Wang,
Xuemei Hu,
Jindan Liu,
Suzheng Zhang,
Jinli Suo,
Guohai Situ
Publication year - 2015
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.23.028416
Subject(s) - ghost imaging , iterative reconstruction , optics , fourier transform , integral imaging , computer science , image restoration , perspective (graphical) , spatial frequency , image quality , image (mathematics) , algorithm , noise (video) , artificial intelligence , image processing , nonlinear system , computer vision , physics , quantum mechanics
Correlation is widely used to reconstruct the object image in ghost imaging (GI). But it only offers a linear proportion of the signal-to-noise ratios (SNR) to the number of measurements. We develop a Gerchberg-Saxton-like technique for GI image reconstruction in this manuscript. The proposed technique takes the advantage of the integral property of the Fourier transform, and treat the captured data as constraints for image reconstruction. We numerically and experimentally demonstrate the technique, and observe a nonlinear growth of the SNR value with respect to the number of measurements in the simulation. The proposed technique provides a different perspective of image reconstruction of GI, and will be beneficial to further explore its potential.