High-Quality Computational Ghost Imaging Using an Optimum Distance Search Method
We propose an optimum distance search method for realizing high-quality computational ghost imaging (CGI). The proposed method, which utilizes the advantages of compressive sensing and the CGI technique, is composed of two search steps. The first step is a coarse search, and the second is a fine sea...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2016-01-01
|
| Series: | IEEE Photonics Journal |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/7765108/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850081840538320896 |
|---|---|
| author | Heng Wu Xianmin Zhang Jinqiang Gan Chunling Luo |
| author_facet | Heng Wu Xianmin Zhang Jinqiang Gan Chunling Luo |
| author_sort | Heng Wu |
| collection | DOAJ |
| description | We propose an optimum distance search method for realizing high-quality computational ghost imaging (CGI). The proposed method, which utilizes the advantages of compressive sensing and the CGI technique, is composed of two search steps. The first step is a coarse search, and the second is a fine search. By using the two-step search, an optimum distance can be obtained. The signal-to-noise ratio (SNR) and the relative mean square error (RMSE) are used as criteria during the search process. Both simulation and experimental results demonstrate that the proposed method can enhance imaging quality, and compressive CGI is more sensitive to distance variations than traditional CGI. The SNR and RMSE are improved when the object is at the optimum distance. |
| format | Article |
| id | doaj-art-36d405b83b924dfaab81b38fbd7e6875 |
| institution | DOAJ |
| issn | 1943-0655 |
| language | English |
| publishDate | 2016-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Photonics Journal |
| spelling | doaj-art-36d405b83b924dfaab81b38fbd7e68752025-08-20T02:44:39ZengIEEEIEEE Photonics Journal1943-06552016-01-01861910.1109/JPHOT.2016.26338677765108High-Quality Computational Ghost Imaging Using an Optimum Distance Search MethodHeng Wu0Xianmin Zhang1Jinqiang Gan2Chunling Luo3Guangdong Provincial Key Laboratory of Precision Equipment and Manufacturing Technology, School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, ChinaGuangdong Provincial Key Laboratory of Precision Equipment and Manufacturing Technology, School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, ChinaGuangdong Provincial Key Laboratory of Precision Equipment and Manufacturing Technology, School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, ChinaDepartment of Applied Physics, East China Jiaotong University, Nanchang, ChinaWe propose an optimum distance search method for realizing high-quality computational ghost imaging (CGI). The proposed method, which utilizes the advantages of compressive sensing and the CGI technique, is composed of two search steps. The first step is a coarse search, and the second is a fine search. By using the two-step search, an optimum distance can be obtained. The signal-to-noise ratio (SNR) and the relative mean square error (RMSE) are used as criteria during the search process. Both simulation and experimental results demonstrate that the proposed method can enhance imaging quality, and compressive CGI is more sensitive to distance variations than traditional CGI. The SNR and RMSE are improved when the object is at the optimum distance.https://ieeexplore.ieee.org/document/7765108/Ghost imagingcomputational imagingimage reconstruction techniquescompressive sensing |
| spellingShingle | Heng Wu Xianmin Zhang Jinqiang Gan Chunling Luo High-Quality Computational Ghost Imaging Using an Optimum Distance Search Method IEEE Photonics Journal Ghost imaging computational imaging image reconstruction techniques compressive sensing |
| title | High-Quality Computational Ghost Imaging Using an Optimum Distance Search Method |
| title_full | High-Quality Computational Ghost Imaging Using an Optimum Distance Search Method |
| title_fullStr | High-Quality Computational Ghost Imaging Using an Optimum Distance Search Method |
| title_full_unstemmed | High-Quality Computational Ghost Imaging Using an Optimum Distance Search Method |
| title_short | High-Quality Computational Ghost Imaging Using an Optimum Distance Search Method |
| title_sort | high quality computational ghost imaging using an optimum distance search method |
| topic | Ghost imaging computational imaging image reconstruction techniques compressive sensing |
| url | https://ieeexplore.ieee.org/document/7765108/ |
| work_keys_str_mv | AT hengwu highqualitycomputationalghostimagingusinganoptimumdistancesearchmethod AT xianminzhang highqualitycomputationalghostimagingusinganoptimumdistancesearchmethod AT jinqianggan highqualitycomputationalghostimagingusinganoptimumdistancesearchmethod AT chunlingluo highqualitycomputationalghostimagingusinganoptimumdistancesearchmethod |