Enhanced Single Pixel Imaging in Atmospheric Turbulence

Yin Cheng; Yusen Liao; Shuaijun Zhou; Jingan Chen; Edmund Y. Lam; Jun Ke

doi:10.1364/COSI.2024.CF1B.5

Enhanced Single Pixel Imaging in Atmospheric Turbulence

Yin Cheng
, Yusen Liao
, Shuaijun Zhou
, Jingan Chen
, Edmund Y. Lam
, Jun Ke^*

^*此作品的通讯作者

光电学院

Beijing Institute of Technology
China Aerospace Science and Technology Corporation
The University of Hong Kong

科研成果: 会议稿件 › 论文 › 同行评审

2 引用（Scopus）

摘要

The imaging quality of single pixel imaging in atmospheric turbulence is enhanced by combining a deep learning model with classical methods. The effectiveness of this method was confirmed by optical experiments.

源语言	英语
DOI	https://doi.org/10.1364/COSI.2024.CF1B.5
出版状态	已出版 - 2024
活动	Computational Optical Sensing and Imaging, COSI 2024 - Part of Optica Imaging Congress - Toulouse, 法国期限: 15 7月 2024 → 19 7月 2024

会议

会议	Computational Optical Sensing and Imaging, COSI 2024 - Part of Optica Imaging Congress
国家/地区	法国
市	Toulouse
时期	15/07/24 → 19/07/24

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10.1364/COSI.2024.CF1B.5

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引用此

@conference{0c409ddbea044c2f86b58140f64adac9,

title = "Enhanced Single Pixel Imaging in Atmospheric Turbulence",

abstract = "The imaging quality of single pixel imaging in atmospheric turbulence is enhanced by combining a deep learning model with classical methods. The effectiveness of this method was confirmed by optical experiments.",

author = "Yin Cheng and Yusen Liao and Shuaijun Zhou and Jingan Chen and Lam, \{Edmund Y.\} and Jun Ke",

note = "Publisher Copyright: {\textcopyright} 2024 The Author(s).; Computational Optical Sensing and Imaging, COSI 2024 - Part of Optica Imaging Congress ; Conference date: 15-07-2024 Through 19-07-2024",

year = "2024",

doi = "10.1364/COSI.2024.CF1B.5",

language = "English",

}

TY - CONF

T1 - Enhanced Single Pixel Imaging in Atmospheric Turbulence

AU - Cheng, Yin

AU - Liao, Yusen

AU - Zhou, Shuaijun

AU - Chen, Jingan

AU - Lam, Edmund Y.

AU - Ke, Jun

PY - 2024

Y1 - 2024

N2 - The imaging quality of single pixel imaging in atmospheric turbulence is enhanced by combining a deep learning model with classical methods. The effectiveness of this method was confirmed by optical experiments.

AB - The imaging quality of single pixel imaging in atmospheric turbulence is enhanced by combining a deep learning model with classical methods. The effectiveness of this method was confirmed by optical experiments.

UR - https://www.scopus.com/pages/publications/85204880531

U2 - 10.1364/COSI.2024.CF1B.5

DO - 10.1364/COSI.2024.CF1B.5

M3 - Paper

AN - SCOPUS:85204880531

T2 - Computational Optical Sensing and Imaging, COSI 2024 - Part of Optica Imaging Congress

Y2 - 15 July 2024 through 19 July 2024

ER -

Enhanced Single Pixel Imaging in Atmospheric Turbulence

摘要

会议

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