kth.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Imaging through a multimode optical fiber with principal component analysis and a variational autoencoder
Mechanical Engineering Department, Southeast University, Nanjing, Jiangsu Province 211189, People’s Republic of China, Jiangsu Province.
KTH, School of Electrical Engineering and Computer Science (EECS).ORCID iD: 0009-0006-6337-4650
Mechanical Engineering Department, Southeast University, Nanjing, Jiangsu Province 211189, People’s Republic of China, Jiangsu Province.
2024 (English)In: Journal of Optics, ISSN 2040-8978, E-ISSN 2040-8986, Vol. 26, no 4, article id 045701Article in journal (Refereed) Published
Abstract [en]

Imaging through the multi-mode fiber (MMF) becomes an attractive approach for gaining visual access to confined spaces. However, current imaging techniques through a MMF still encounter challenges including modal dispersion, complex wave-front shaping mechanism, and expensive light sources and modulations. This work proposed a cost-efficient setup with three light-emitting diodes as the illumination light source (including red, green, and blue light) and a hybrid model including the principal component analysis and a variational auto-encoder (PCAVAE) for reconstructing the transmitted images. The reconstructed images demonstrate high fidelity compared with their ground truth images. The average similarity index value of the reconstructed images is as high as 0.99. Experimental works indicated that the proposed approach was capable of rejecting 10% white noise in the imaging process. The proposed triple-color illumination method paves a cost-effective way of transmitting images through an MMF. The PCAVAE model established in this work demonstrates great potential for processing scrambled images transmitted by the MMF.

Place, publisher, year, edition, pages
IOP Publishing , 2024. Vol. 26, no 4, article id 045701
Keywords [en]
imaging, machine learning, mulit-mode optical fiber
National Category
Computer graphics and computer vision
Identifiers
URN: urn:nbn:se:kth:diva-344185DOI: 10.1088/2040-8986/ad2a22ISI: 001174190000001Scopus ID: 2-s2.0-85186116662OAI: oai:DiVA.org:kth-344185DiVA, id: diva2:1842905
Note

QC 20240318

Available from: 2024-03-06 Created: 2024-03-06 Last updated: 2025-02-07Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Che, Zifan

Search in DiVA

By author/editor
Che, Zifan
By organisation
School of Electrical Engineering and Computer Science (EECS)
In the same journal
Journal of Optics
Computer graphics and computer vision

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 14 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf