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Multi-scale Adaptive Computational Ghost Imaging

In some cases of imaging, wide spatial range and high spatial resolution are both required, which requests high performance of detection devices and huge resource consumption for data processing. We propose and demonstrate a multi-scale adaptive imaging method based on the idea of computational ghos...

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Detalles Bibliográficos
Autores principales: Sun, Shuai, Liu, Wei-Tao, Lin, Hui-Zu, Zhang, Er-Feng, Liu, Ji-Ying, Li, Quan, Chen, Ping-Xing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5107932/
https://www.ncbi.nlm.nih.gov/pubmed/27841339
http://dx.doi.org/10.1038/srep37013
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author Sun, Shuai
Liu, Wei-Tao
Lin, Hui-Zu
Zhang, Er-Feng
Liu, Ji-Ying
Li, Quan
Chen, Ping-Xing
author_facet Sun, Shuai
Liu, Wei-Tao
Lin, Hui-Zu
Zhang, Er-Feng
Liu, Ji-Ying
Li, Quan
Chen, Ping-Xing
author_sort Sun, Shuai
collection PubMed
description In some cases of imaging, wide spatial range and high spatial resolution are both required, which requests high performance of detection devices and huge resource consumption for data processing. We propose and demonstrate a multi-scale adaptive imaging method based on the idea of computational ghost imaging, which can obtain a rough outline of the whole scene with a wide range then accordingly find out the interested parts and achieve high-resolution details of those parts, by controlling the field of view and the transverse coherence width of the pseudo-thermal field illuminated on the scene with a spatial light modulator. Compared to typical ghost imaging, the resource consumption can be dramatically reduced using our scheme.
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spelling pubmed-51079322016-11-22 Multi-scale Adaptive Computational Ghost Imaging Sun, Shuai Liu, Wei-Tao Lin, Hui-Zu Zhang, Er-Feng Liu, Ji-Ying Li, Quan Chen, Ping-Xing Sci Rep Article In some cases of imaging, wide spatial range and high spatial resolution are both required, which requests high performance of detection devices and huge resource consumption for data processing. We propose and demonstrate a multi-scale adaptive imaging method based on the idea of computational ghost imaging, which can obtain a rough outline of the whole scene with a wide range then accordingly find out the interested parts and achieve high-resolution details of those parts, by controlling the field of view and the transverse coherence width of the pseudo-thermal field illuminated on the scene with a spatial light modulator. Compared to typical ghost imaging, the resource consumption can be dramatically reduced using our scheme. Nature Publishing Group 2016-11-14 /pmc/articles/PMC5107932/ /pubmed/27841339 http://dx.doi.org/10.1038/srep37013 Text en Copyright © 2016, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Sun, Shuai
Liu, Wei-Tao
Lin, Hui-Zu
Zhang, Er-Feng
Liu, Ji-Ying
Li, Quan
Chen, Ping-Xing
Multi-scale Adaptive Computational Ghost Imaging
title Multi-scale Adaptive Computational Ghost Imaging
title_full Multi-scale Adaptive Computational Ghost Imaging
title_fullStr Multi-scale Adaptive Computational Ghost Imaging
title_full_unstemmed Multi-scale Adaptive Computational Ghost Imaging
title_short Multi-scale Adaptive Computational Ghost Imaging
title_sort multi-scale adaptive computational ghost imaging
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5107932/
https://www.ncbi.nlm.nih.gov/pubmed/27841339
http://dx.doi.org/10.1038/srep37013
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