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Hidden-information extraction from layered structures through terahertz imaging down to ultralow SNR

Noninvasive inspection of layered structures has remained a long-standing challenge for time-resolved imaging techniques, where both resolution and contrast are compromised by prominent signal attenuation, interlayer reflections, and dispersion. Our method based on terahertz (THz) time-domain spectr...

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Autores principales: Cui, Yuqing, Xu, Yafei, Han, Donghai, Wang, Xingyu, Shen, Zhonglei, Hou, Yushan, Liang, Junyan, Wang, Xianqiao, Citrin, David S., Zhang, Liuyang, Nandi, Asoke K., Yan, Ruqiang, Chen, Xuefeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for the Advancement of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10550239/
https://www.ncbi.nlm.nih.gov/pubmed/37792928
http://dx.doi.org/10.1126/sciadv.adg8435
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author Cui, Yuqing
Xu, Yafei
Han, Donghai
Wang, Xingyu
Shen, Zhonglei
Hou, Yushan
Liang, Junyan
Wang, Xianqiao
Citrin, David S.
Zhang, Liuyang
Nandi, Asoke K.
Yan, Ruqiang
Chen, Xuefeng
author_facet Cui, Yuqing
Xu, Yafei
Han, Donghai
Wang, Xingyu
Shen, Zhonglei
Hou, Yushan
Liang, Junyan
Wang, Xianqiao
Citrin, David S.
Zhang, Liuyang
Nandi, Asoke K.
Yan, Ruqiang
Chen, Xuefeng
author_sort Cui, Yuqing
collection PubMed
description Noninvasive inspection of layered structures has remained a long-standing challenge for time-resolved imaging techniques, where both resolution and contrast are compromised by prominent signal attenuation, interlayer reflections, and dispersion. Our method based on terahertz (THz) time-domain spectroscopy overcomes these limitations by offering fine resolution and a broadband spectrum to efficiently extract hidden structural and content information from layered structures. We exploit local symmetrical characteristics of reflected THz pulses to determine the location of each layer, and apply a statistical process in the spatiotemporal domain to enhance the image contrast. Its superior performance is evidenced by the extraction of alphabetic characters in 26-layer subwavelength papers as well as layer reconstruction and debonding inspection in the conservation of Terra-Cotta Warriors. Our method enables accurate structure reconstruction and high-contrast imaging of layered structures at ultralow signal-to-noise ratio, which holds great potential for internal inspection of cultural artifacts, electronic components, coatings, and composites with dozens of submillimeter layers.
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spelling pubmed-105502392023-10-05 Hidden-information extraction from layered structures through terahertz imaging down to ultralow SNR Cui, Yuqing Xu, Yafei Han, Donghai Wang, Xingyu Shen, Zhonglei Hou, Yushan Liang, Junyan Wang, Xianqiao Citrin, David S. Zhang, Liuyang Nandi, Asoke K. Yan, Ruqiang Chen, Xuefeng Sci Adv Physical and Materials Sciences Noninvasive inspection of layered structures has remained a long-standing challenge for time-resolved imaging techniques, where both resolution and contrast are compromised by prominent signal attenuation, interlayer reflections, and dispersion. Our method based on terahertz (THz) time-domain spectroscopy overcomes these limitations by offering fine resolution and a broadband spectrum to efficiently extract hidden structural and content information from layered structures. We exploit local symmetrical characteristics of reflected THz pulses to determine the location of each layer, and apply a statistical process in the spatiotemporal domain to enhance the image contrast. Its superior performance is evidenced by the extraction of alphabetic characters in 26-layer subwavelength papers as well as layer reconstruction and debonding inspection in the conservation of Terra-Cotta Warriors. Our method enables accurate structure reconstruction and high-contrast imaging of layered structures at ultralow signal-to-noise ratio, which holds great potential for internal inspection of cultural artifacts, electronic components, coatings, and composites with dozens of submillimeter layers. American Association for the Advancement of Science 2023-10-04 /pmc/articles/PMC10550239/ /pubmed/37792928 http://dx.doi.org/10.1126/sciadv.adg8435 Text en Copyright © 2023 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license (https://creativecommons.org/licenses/by-nc/4.0/) , which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited.
spellingShingle Physical and Materials Sciences
Cui, Yuqing
Xu, Yafei
Han, Donghai
Wang, Xingyu
Shen, Zhonglei
Hou, Yushan
Liang, Junyan
Wang, Xianqiao
Citrin, David S.
Zhang, Liuyang
Nandi, Asoke K.
Yan, Ruqiang
Chen, Xuefeng
Hidden-information extraction from layered structures through terahertz imaging down to ultralow SNR
title Hidden-information extraction from layered structures through terahertz imaging down to ultralow SNR
title_full Hidden-information extraction from layered structures through terahertz imaging down to ultralow SNR
title_fullStr Hidden-information extraction from layered structures through terahertz imaging down to ultralow SNR
title_full_unstemmed Hidden-information extraction from layered structures through terahertz imaging down to ultralow SNR
title_short Hidden-information extraction from layered structures through terahertz imaging down to ultralow SNR
title_sort hidden-information extraction from layered structures through terahertz imaging down to ultralow snr
topic Physical and Materials Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10550239/
https://www.ncbi.nlm.nih.gov/pubmed/37792928
http://dx.doi.org/10.1126/sciadv.adg8435
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