Combined optimization ghost imaging based on random speckle field

Type: Preprint

Publication Date: 2024-03-05

Citations: 0

DOI: https://doi.org/10.48550/arxiv.2403.03426

View Chat PDF

Abstract

Ghost imaging is a non local imaging technology, which can obtain target information by measuring the second-order intensity correlation between the reference light field and the target detection light field. However, the current imaging environment requires a large number of measurement data, and the imaging results also have the problems of low image resolution and long reconstruction time. Therefore, using orthogonal methods such as QR decomposition, a variety of optimization methods for speckle patterns are designed combined with Kronecker product,which can help to shorten the imaging time, improve the imaging quality and image noise resistance.

Locations

  • arXiv (Cornell University) - View - PDF

Similar Works

Action Title Year Authors
+ PDF Chat Optimizing ghost imaging via analysis and design of speckle patterns 2022 Xinjian Zhang
Siyuan Song
Xiaoping Ma
Haonan Zhang
Lei Gai
Yongjian Gu
Wendong Li
+ Optimization of retina-like illumination patterns in ghost imaging 2021 Jie Cao
Dong Zhou
Yingqiang Zhang
Huan Cui
Fanghua Zhang
Qun Hao
+ Optimization of retina-like illumination patterns in ghost imaging 2021 Jie Cao
Dong Zhou
Yingqiang Zhang
Huan Cui
Fanghua Zhang
Kaiyu Zhang
Qun Hao
+ Noise-free computational ghost imaging with pink noise speckle patterns 2020 Xiaoyu Nie
Fan Yang
Xiangpei Liu
Xingchen Zhao
Reed Nessler
Zheng Li
Tao Peng
M. Suhail Zubairy
Marlan O. Scully
+ Gold Matrix Ghost Imaging 2019 Xiwei Zhao
Xue Wang
Wenying Zhang
Shanshan Jia
Cheng Zhou
Lijun Song
+ Edge detection based on joint iteration ghost imaging 2019 Cheng Zhou
Gangcheng Wang
Heyan Huang
Lijun Song
Kang Xue
+ Optimization of light fields in ghost imaging using dictionary learning 2019 Chenyu Hu
Zhishen Tong
Zhentao Liu
Zengfeng Huang
Jian Wang
Shensheng Han
+ Robust data analysis and imaging with computational ghost imaging 2021 Jiangtao Liu
Xunming Cai
Jinbao Huang
Kun Luo
HongXu Li
Weimin Li
Dejian Zhang
Zhenhua Wu
+ Anti-scattering medium computational ghost imaging with modified Hadamard patterns 2023 Lixing Lin
Jie Cao
Qun Hao
+ PDF Chat Encryption in ghost imaging with Kronecker products of random matrices 2024 Yining Zhao
Lin-Shan Chen
Lingxin Kong
Chong Wang
Cheng Ren
De-Zhong Cao
+ Ghost Imaging Based on Recurrent Neural Network 2021 Yuchen He
Sihong Duan
Jianxing Li
Hui Chen
Huaibin Zheng
Jianbin Liu
Yu Zhou
Zhuo Xu
+ Phase retrieval based on shaped incoherent sources 2022 Ziyan Chen
Heng wu
Jing Cheng
+ Breaking Rayleigh's Criterion via Discernibility in High-Dimensional Light-Field Space with Snapshot Ghost Imaging 2020 Zhishen Tong
Zhentao Liu
Jian Wang
Xia Shen
Shensheng Han
+ Sub-Nyquist computational ghost imaging with orthonormalized colored noise pattern 2020 Xiaoyu Nie
Xingchen Zhao
Tao Peng
Marlan O. Scully
+ Hadamard `Pipeline' Coding Computational Ghost Imaging 2019 Cheng Zhou
Xiwei Zhao
Heyan Huang
Gangcheng Wang
Xue Wang
Lijun Song
Kang Xue
+ Dual-mode adaptive-SVD ghost imaging 2023 Dajing Wang
Baolei Liu
Jiaqi Song
Yao Wang
Xuchen Shan
Xiaolan Zhong
Fan Wang
+ Dual-mode adaptive-SVD ghost imaging 2023 Dajing Wang
Baolei Liu
Jiaqi Song
Yao Wang
Xuchen Shan
Fan Wang
+ Unified joint reconstruction approach for random illumination microscopy 2020 Penghuan Liu
+ Instant ghost imaging: improving robustness for ghost imaging subject to optical background noise 2020 Zhe Yang
Weixing Zhang
Ma-Chi Zhang
Dong Ruan
Junlin Li
+ Instant ghost imaging: improving robustness for ghost imaging subject to optical background noise 2020 Zhe Yang
Weixing Zhang
Ma-Chi Zhang
Dong Ruan
Junlin Li

Cited by (0)

Action Title Year Authors

Citing (0)

Action Title Year Authors