Open AccessIterative denoising of ghost imaging
Author(s) -
XuRi Yao,
Wen-Kai Yu,
Xuefeng Liu,
Longzhen Li,
Mingfei Li,
LingAn Wu,
Guangtao Zhai
Publication year - 2014
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.22.024268
Subject(s) - ghost imaging , image quality , noise reduction , speckle noise , optics , speckle pattern , noise (video) , iterative method , computer science , iterative and incremental development , iterative reconstruction , artificial intelligence , image processing , computer vision , image (mathematics) , algorithm , physics , software engineering
We present a new technique to denoise ghost imaging (GI) in which conventional intensity correlation GI and an iteration process have been combined to give an accurate estimate of the actual noise affecting image quality. The blurring influence of the speckle areas in the beam is reduced in the iteration by setting a threshold. It is shown that with an appropriate choice of threshold value, the quality of the iterative GI reconstructed image is much better than that of differential GI for the same number of measurements. This denoising method thus offers a very effective approach to promote the implementation of GI in real applications.