Noise reduction in computational ghost imaging by interpolated monitoring

Zhaohua Yang; Yuzhe Sun; Shaofan Qu; Yuanjin Yu; Ruitao Yan; Ai Xin Zhang; Ling An Wu

doi:10.1364/AO.57.006097

Noise reduction in computational ghost imaging by interpolated monitoring

Zhaohua Yang^*, Yuzhe Sun, Shaofan Qu, Yuanjin Yu, Ruitao Yan, Ai Xin Zhang, Ling An Wu

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

9 Citations (Scopus)

Abstract

An interpolation computational ghost imaging (ICGI) method is proposed and demonstrated that is able to reduce the noise interference from a fluctuating source and background. The noise is estimated through periodic illuminations by a specific assay pattern during sampling, which is then used to correct the bucket detector signal. To validate this method simulations and experiments were conducted. Light source intensity and background lighting were randomly varied to modulate the noise. The results show that good quality images can be obtained, while with conventional computational ghost imaging (CGI) the reconstructed object is barely recognizable. The ICGI method offers a general approach applicable to all CGI techniques, which can attenuate the interference from source fluctuations, background light noise, dynamic scattering, and so on.

Original language	English
Pages (from-to)	6097-6101
Number of pages	5
Journal	Applied Optics
Volume	57
Issue number	21
DOIs	https://doi.org/10.1364/AO.57.006097
Publication status	Published - 20 Jul 2018
Externally published	Yes

Access to Document

10.1364/AO.57.006097

Cite this

@article{dc6dc976dbaa47cbae819292347cfd4c,

title = "Noise reduction in computational ghost imaging by interpolated monitoring",

abstract = "An interpolation computational ghost imaging (ICGI) method is proposed and demonstrated that is able to reduce the noise interference from a fluctuating source and background. The noise is estimated through periodic illuminations by a specific assay pattern during sampling, which is then used to correct the bucket detector signal. To validate this method simulations and experiments were conducted. Light source intensity and background lighting were randomly varied to modulate the noise. The results show that good quality images can be obtained, while with conventional computational ghost imaging (CGI) the reconstructed object is barely recognizable. The ICGI method offers a general approach applicable to all CGI techniques, which can attenuate the interference from source fluctuations, background light noise, dynamic scattering, and so on.",

author = "Zhaohua Yang and Yuzhe Sun and Shaofan Qu and Yuanjin Yu and Ruitao Yan and Zhang, {Ai Xin} and Wu, {Ling An}",

note = "Publisher Copyright: {\textcopyright} 2018 Optical Society of America.",

year = "2018",

month = jul,

day = "20",

doi = "10.1364/AO.57.006097",

language = "English",

volume = "57",

pages = "6097--6101",

journal = "Applied Optics",

issn = "1559-128X",

publisher = "Optica Publishing Group",

number = "21",

}

TY - JOUR

T1 - Noise reduction in computational ghost imaging by interpolated monitoring

AU - Yang, Zhaohua

AU - Sun, Yuzhe

AU - Qu, Shaofan

AU - Yu, Yuanjin

AU - Yan, Ruitao

AU - Zhang, Ai Xin

AU - Wu, Ling An

PY - 2018/7/20

Y1 - 2018/7/20

N2 - An interpolation computational ghost imaging (ICGI) method is proposed and demonstrated that is able to reduce the noise interference from a fluctuating source and background. The noise is estimated through periodic illuminations by a specific assay pattern during sampling, which is then used to correct the bucket detector signal. To validate this method simulations and experiments were conducted. Light source intensity and background lighting were randomly varied to modulate the noise. The results show that good quality images can be obtained, while with conventional computational ghost imaging (CGI) the reconstructed object is barely recognizable. The ICGI method offers a general approach applicable to all CGI techniques, which can attenuate the interference from source fluctuations, background light noise, dynamic scattering, and so on.

AB - An interpolation computational ghost imaging (ICGI) method is proposed and demonstrated that is able to reduce the noise interference from a fluctuating source and background. The noise is estimated through periodic illuminations by a specific assay pattern during sampling, which is then used to correct the bucket detector signal. To validate this method simulations and experiments were conducted. Light source intensity and background lighting were randomly varied to modulate the noise. The results show that good quality images can be obtained, while with conventional computational ghost imaging (CGI) the reconstructed object is barely recognizable. The ICGI method offers a general approach applicable to all CGI techniques, which can attenuate the interference from source fluctuations, background light noise, dynamic scattering, and so on.

UR - http://www.scopus.com/inward/record.url?scp=85050211756&partnerID=8YFLogxK

U2 - 10.1364/AO.57.006097

DO - 10.1364/AO.57.006097

M3 - Article

C2 - 30118039

AN - SCOPUS:85050211756

SN - 1559-128X

VL - 57

SP - 6097

EP - 6101

JO - Applied Optics

JF - Applied Optics

IS - 21

ER -

Noise reduction in computational ghost imaging by interpolated monitoring

Abstract

Access to Document

Other files and links

Fingerprint

Cite this