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Three-Dimensional (3D) Visualization under Extremely Low Light Conditions Using Kalman Filter
In recent years, research on three-dimensional (3D) reconstruction under low illumination environment has been reported. Photon-counting integral imaging is one of the techniques for visualizing 3D images under low light conditions. However, conventional photon-counting integral imaging has the prob...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10490719/ https://www.ncbi.nlm.nih.gov/pubmed/37688025 http://dx.doi.org/10.3390/s23177571 |
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author | Kim, Hyun-Woo Cho, Myungjin Lee, Min-Chul |
author_facet | Kim, Hyun-Woo Cho, Myungjin Lee, Min-Chul |
author_sort | Kim, Hyun-Woo |
collection | PubMed |
description | In recent years, research on three-dimensional (3D) reconstruction under low illumination environment has been reported. Photon-counting integral imaging is one of the techniques for visualizing 3D images under low light conditions. However, conventional photon-counting integral imaging has the problem that results are random because Poisson random numbers are temporally and spatially independent. Therefore, in this paper, we apply a technique called Kalman filter to photon-counting integral imaging, which corrects data groups with errors, to improve the visual quality of results. The purpose of this paper is to reduce randomness and improve the accuracy of visualization for results by incorporating the Kalman filter into 3D reconstruction images under extremely low light conditions. Since the proposed method has better structure similarity (SSIM), peak signal-to-noise ratio (PSNR) and cross-correlation values than the conventional method, it can be said that the visualization of low illuminated images can be accurate. In addition, the proposed method is expected to accelerate the development of autonomous driving technology and security camera technology. |
format | Online Article Text |
id | pubmed-10490719 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-104907192023-09-09 Three-Dimensional (3D) Visualization under Extremely Low Light Conditions Using Kalman Filter Kim, Hyun-Woo Cho, Myungjin Lee, Min-Chul Sensors (Basel) Article In recent years, research on three-dimensional (3D) reconstruction under low illumination environment has been reported. Photon-counting integral imaging is one of the techniques for visualizing 3D images under low light conditions. However, conventional photon-counting integral imaging has the problem that results are random because Poisson random numbers are temporally and spatially independent. Therefore, in this paper, we apply a technique called Kalman filter to photon-counting integral imaging, which corrects data groups with errors, to improve the visual quality of results. The purpose of this paper is to reduce randomness and improve the accuracy of visualization for results by incorporating the Kalman filter into 3D reconstruction images under extremely low light conditions. Since the proposed method has better structure similarity (SSIM), peak signal-to-noise ratio (PSNR) and cross-correlation values than the conventional method, it can be said that the visualization of low illuminated images can be accurate. In addition, the proposed method is expected to accelerate the development of autonomous driving technology and security camera technology. MDPI 2023-08-31 /pmc/articles/PMC10490719/ /pubmed/37688025 http://dx.doi.org/10.3390/s23177571 Text en © 2023 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 Kim, Hyun-Woo Cho, Myungjin Lee, Min-Chul Three-Dimensional (3D) Visualization under Extremely Low Light Conditions Using Kalman Filter |
title | Three-Dimensional (3D) Visualization under Extremely Low Light Conditions Using Kalman Filter |
title_full | Three-Dimensional (3D) Visualization under Extremely Low Light Conditions Using Kalman Filter |
title_fullStr | Three-Dimensional (3D) Visualization under Extremely Low Light Conditions Using Kalman Filter |
title_full_unstemmed | Three-Dimensional (3D) Visualization under Extremely Low Light Conditions Using Kalman Filter |
title_short | Three-Dimensional (3D) Visualization under Extremely Low Light Conditions Using Kalman Filter |
title_sort | three-dimensional (3d) visualization under extremely low light conditions using kalman filter |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10490719/ https://www.ncbi.nlm.nih.gov/pubmed/37688025 http://dx.doi.org/10.3390/s23177571 |
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