Object Reconstruction Using the Binomial Theorem for Ghost Imaging

Noise term in the reconstruction matrix in ghost imaging is a major cause of blurring imaging results. To remedy this problem, we propose a new ghost imaging method based on the binomial theorem to reduce the level of noise. In our method, images with low-level noise can be generated by constructing...

Full description

Saved in:
Bibliographic Details
Published in:IEEE photonics journal 2018-12, Vol.10 (6), p.1-13
Main Authors: Yue, Cong, Chen, Ping, Lv, Xiaofeng, Wang, Chenglong, Guo, Shuxu, Song, Junfeng, Gong, Wenlin, Gao, Fengli
Format: Article
Language:English
Subjects:
Binomial theorem
Blurring
coherence imaging
Computer simulation
Computing time
Image processing
Image reconstruction
Imaging processing
Laser beams
Noise
Noise level
Noise reduction
photon statistics
quantum optics
Speckle
Theorems
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Noise term in the reconstruction matrix in ghost imaging is a major cause of blurring imaging results. To remedy this problem, we propose a new ghost imaging method based on the binomial theorem to reduce the level of noise. In our method, images with low-level noise can be generated by constructing a binomial formula using high-order imaging results that are acquired by reintroducing the reconstruction result back into the imaging formula repeatedly. Experimental and simulation results demonstrate that our method is effective in improving imaging quality and the anti-interference performance and reducing computing time, making it useful for practical applications.
ISSN:1943-0655
1943-0647
DOI:10.1109/JPHOT.2018.2880430