| タイトル |
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en
Three-Dimensional (3D) Visualization under Extremely Low Light Conditions Using Kalman Filter
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| 作成者 |
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en
Lee, Min-Chul
ja
李, 旻哲
ja-Kana
イ, ミンチョル
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e-Rad 60363397
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| 権利情報 |
- https://creativecommons.org/licenses/by/4.0/
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Copyright (c) 2023 by the authors. 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.
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| 主題 |
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Other
digital image processing
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Other
integral imaging
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Other
Kalman filter
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Other
photon-counting integral imaging
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Other
volumetric computational reconstruction
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| 内容注記 |
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Abstract
en
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.
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| 出版者 |
MDPI
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| 日付 |
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| 言語 |
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| 資源タイプ |
journal article |
| 出版タイプ |
VoR |
| 資源識別子 |
HDL
http://hdl.handle.net/10228/0002000108
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URI
https://kyutech.repo.nii.ac.jp/records/2000108
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| 関連 |
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isIdenticalTo
DOI
https://doi.org/10.3390/s23177571
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| 収録誌情報 |
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en
Sensors
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巻23
号17
開始ページ7571
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| ファイル |
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| コンテンツ更新日時 |
2025-07-14 |
