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Polarization Super-Resolution Imaging Method Based on Deep Compressed Sensing

The division of focal plane (DoFP) polarization imaging sensors, which can simultaneously acquire the target’s two-dimensional spatial information and polarization information, improves the detection resolution and recognition capability by capturing the difference in polarization characteristics be...

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Detalles Bibliográficos
Autores principales: Xu, Miao, Wang, Chao, Wang, Kaikai, Shi, Haodong, Li, Yingchao, Jiang, Huilin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9783235/
https://www.ncbi.nlm.nih.gov/pubmed/36560044
http://dx.doi.org/10.3390/s22249676
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author Xu, Miao
Wang, Chao
Wang, Kaikai
Shi, Haodong
Li, Yingchao
Jiang, Huilin
author_facet Xu, Miao
Wang, Chao
Wang, Kaikai
Shi, Haodong
Li, Yingchao
Jiang, Huilin
author_sort Xu, Miao
collection PubMed
description The division of focal plane (DoFP) polarization imaging sensors, which can simultaneously acquire the target’s two-dimensional spatial information and polarization information, improves the detection resolution and recognition capability by capturing the difference in polarization characteristics between the target and the background. In this paper, we propose a novel polarization imaging method based on deep compressed sensing (DCS) by adding digital micromirror devices (DMD) to an optical system and simulating the polarization transmission model of the optical system to reconstruct high-resolution images under low sampling rate conditions. By building a simulated dataset, training a polarization super-resolution imaging network, and showing excellent reconstructions on real shooting scenes, compared to current algorithms, our model has a higher peak signal-to-noise ratio (PSNR), which validates the feasibility of our approach.
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spelling pubmed-97832352022-12-24 Polarization Super-Resolution Imaging Method Based on Deep Compressed Sensing Xu, Miao Wang, Chao Wang, Kaikai Shi, Haodong Li, Yingchao Jiang, Huilin Sensors (Basel) Article The division of focal plane (DoFP) polarization imaging sensors, which can simultaneously acquire the target’s two-dimensional spatial information and polarization information, improves the detection resolution and recognition capability by capturing the difference in polarization characteristics between the target and the background. In this paper, we propose a novel polarization imaging method based on deep compressed sensing (DCS) by adding digital micromirror devices (DMD) to an optical system and simulating the polarization transmission model of the optical system to reconstruct high-resolution images under low sampling rate conditions. By building a simulated dataset, training a polarization super-resolution imaging network, and showing excellent reconstructions on real shooting scenes, compared to current algorithms, our model has a higher peak signal-to-noise ratio (PSNR), which validates the feasibility of our approach. MDPI 2022-12-10 /pmc/articles/PMC9783235/ /pubmed/36560044 http://dx.doi.org/10.3390/s22249676 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Xu, Miao
Wang, Chao
Wang, Kaikai
Shi, Haodong
Li, Yingchao
Jiang, Huilin
Polarization Super-Resolution Imaging Method Based on Deep Compressed Sensing
title Polarization Super-Resolution Imaging Method Based on Deep Compressed Sensing
title_full Polarization Super-Resolution Imaging Method Based on Deep Compressed Sensing
title_fullStr Polarization Super-Resolution Imaging Method Based on Deep Compressed Sensing
title_full_unstemmed Polarization Super-Resolution Imaging Method Based on Deep Compressed Sensing
title_short Polarization Super-Resolution Imaging Method Based on Deep Compressed Sensing
title_sort polarization super-resolution imaging method based on deep compressed sensing
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9783235/
https://www.ncbi.nlm.nih.gov/pubmed/36560044
http://dx.doi.org/10.3390/s22249676
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AT shihaodong polarizationsuperresolutionimagingmethodbasedondeepcompressedsensing
AT liyingchao polarizationsuperresolutionimagingmethodbasedondeepcompressedsensing
AT jianghuilin polarizationsuperresolutionimagingmethodbasedondeepcompressedsensing