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Information distribution on regions of speckle patterns for imaging of multimode fiber

Multimode fibers (MMF) have been extensively investigated for transmitting images. The transmitting images are distorted into speckle patterns by MMFs, which can be reconstructed by neural networks. We studied the information distribution of MMF speckle patterns for image reconstruction. The speckle...

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Detalles Bibliográficos
Autores principales: Liu, Shenyi, Sun, Yunxu, Liu, Wei, Xiao, FuChen, Song, Haoyang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9932470/
https://www.ncbi.nlm.nih.gov/pubmed/36816253
http://dx.doi.org/10.1016/j.heliyon.2023.e13357
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author Liu, Shenyi
Sun, Yunxu
Liu, Wei
Xiao, FuChen
Song, Haoyang
author_facet Liu, Shenyi
Sun, Yunxu
Liu, Wei
Xiao, FuChen
Song, Haoyang
author_sort Liu, Shenyi
collection PubMed
description Multimode fibers (MMF) have been extensively investigated for transmitting images. The transmitting images are distorted into speckle patterns by MMFs, which can be reconstructed by neural networks. We studied the information distribution of MMF speckle patterns for image reconstruction. The speckle patterns, segmented by three methods of segmentation, as Centering (1), Quartering (2) and Surrounding (3), are reconstructed into input images by Complex Artificial Neural Network (CANN). Experimental results show that only about one third of full speckle patterns is enough to reconstruct the original images. The quality of reconstructed image is related to the cropping method with different frequency components in speckle patterns, under the same cropped size, Centering segmentation has 4% performance improvement compared to Surrounding segmentation. Optimized segmentation will improve the quality of reconstructed images.
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spelling pubmed-99324702023-02-17 Information distribution on regions of speckle patterns for imaging of multimode fiber Liu, Shenyi Sun, Yunxu Liu, Wei Xiao, FuChen Song, Haoyang Heliyon Research Article Multimode fibers (MMF) have been extensively investigated for transmitting images. The transmitting images are distorted into speckle patterns by MMFs, which can be reconstructed by neural networks. We studied the information distribution of MMF speckle patterns for image reconstruction. The speckle patterns, segmented by three methods of segmentation, as Centering (1), Quartering (2) and Surrounding (3), are reconstructed into input images by Complex Artificial Neural Network (CANN). Experimental results show that only about one third of full speckle patterns is enough to reconstruct the original images. The quality of reconstructed image is related to the cropping method with different frequency components in speckle patterns, under the same cropped size, Centering segmentation has 4% performance improvement compared to Surrounding segmentation. Optimized segmentation will improve the quality of reconstructed images. Elsevier 2023-02-01 /pmc/articles/PMC9932470/ /pubmed/36816253 http://dx.doi.org/10.1016/j.heliyon.2023.e13357 Text en © 2023 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Research Article
Liu, Shenyi
Sun, Yunxu
Liu, Wei
Xiao, FuChen
Song, Haoyang
Information distribution on regions of speckle patterns for imaging of multimode fiber
title Information distribution on regions of speckle patterns for imaging of multimode fiber
title_full Information distribution on regions of speckle patterns for imaging of multimode fiber
title_fullStr Information distribution on regions of speckle patterns for imaging of multimode fiber
title_full_unstemmed Information distribution on regions of speckle patterns for imaging of multimode fiber
title_short Information distribution on regions of speckle patterns for imaging of multimode fiber
title_sort information distribution on regions of speckle patterns for imaging of multimode fiber
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9932470/
https://www.ncbi.nlm.nih.gov/pubmed/36816253
http://dx.doi.org/10.1016/j.heliyon.2023.e13357
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