Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/108994
| Title: | Self-corrected orthonormalized ghost imaging through dynamic and complex scattering media | Authors: | Zhou, L Xiao, Y Chen, W |
Issue Date: | 3-Jul-2023 | Source: | Applied physics letters, 3 July 2023, v. 123, no. 1, 011107 | Abstract: | In this Letter, we report a setup design to realize high-visibility orthonormalized ghost imaging (GI) with self-correction through dynamic and complex scattering media at low sampling ratios. With the design of a parallel detection, a mismatch between illumination patterns and intensity measurements is corrected. Gram–Schmidt orthonormalization is further applied to the illumination patterns and corrected intensities in order to implement high-visibility GI through dynamic and complex scattering media at low sampling ratios. It is experimentally demonstrated that the proposed self-correction and orthonormalization enable high-visibility and high-efficiency GI through dynamic and complex scattering media at low sampling ratios. The proposed method offers a promising alternative to overcome the challenge faced by conventional GI in implementing high-visibility object reconstruction through dynamic and complex scattering media at low sampling ratios. | Publisher: | AIP Publishing LLC | Journal: | Applied physics letters | ISSN: | 0003-6951 | EISSN: | 1077-3118 | DOI: | 10.1063/5.0158244 | Rights: | © 2023 Author(s). Published under an exclusive license by AIP Publishing. This article may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing. This article appeared in Lina Zhou, Yin Xiao, Wen Chen; Self-corrected orthonormalized ghost imaging through dynamic and complex scattering media. Appl. Phys. Lett. 3 July 2023; 123 (1): 011107 and may be found at https://doi.org/10.1063/5.0158244. |
| Appears in Collections: | Journal/Magazine Article |
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| File | Description | Size | Format | |
|---|---|---|---|---|
| 011107_1_5.0158244.pdf | 2.16 MB | Adobe PDF | View/Open |
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