WEKO3
アイテム
Deep Learning-Based Resolution Enhancement of Digital Holograms Using Spatial Frequency Domain Loss Function
http://hdl.handle.net/10228/0002001765
http://hdl.handle.net/10228/00020017654be310c7-156e-4460-9ea0-fb3e4fd83756
| 名前 / ファイル | ライセンス | アクション |
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neuro_107.pdf (223.1 KB)
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| アイテムタイプ | 共通アイテムタイプ(1) | |||||||||||
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| 公開日 | 2025-07-10 | |||||||||||
| タイトル | ||||||||||||
| タイトル | Deep Learning-Based Resolution Enhancement of Digital Holograms Using Spatial Frequency Domain Loss Function | |||||||||||
| 言語 | en | |||||||||||
| 著者 |
Esaki, Ryo
× Esaki, Ryo
× 高林, 正典
WEKO
35482
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| 抄録 | ||||||||||||
| 内容記述タイプ | Abstract | |||||||||||
| 内容記述 | Since the spatial resolution of image sensors used for digital holography is limited and is generally lower than that of photosensitive materials used for optical holography, there is a concern that the high spatial frequency component of the digital hologram is degraded. Therefore, it is desired to use an image sensor with as high a resolution as possible, however such image sensor is generally expensive and have low sensitivity due to their small pixels. To solve this problem, we have focused on the approach which appropriately interpolates the high spatial resolution component by deep learning [1]. In this study, we perform the experiment on off-axis digital holography to investigate the usefulness of deep learning for the resolution enhancement of digital holograms. Specifically, we develop a resolution-enhance deep neural network which is trained by with pairs of digital holograms acquired using image sensors with different spatial resolutions and transforms arbitrary low-resolution digital holograms into high-resolution digital holograms. In particular, we propose to use spatial frequency domain information as the loss function in the deep neural network to achieve further improvement of the resolution enhancement. |
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| 言語 | en | |||||||||||
| 備考 | ||||||||||||
| 内容記述タイプ | Other | |||||||||||
| 内容記述 | International Symposium on Imaging, Sensing, and Optical Memory 2024, ISOM’24, October 20-23, 2024, Arcrea HIMEJI, Himeji, Hyogo, Japan | |||||||||||
| 言語 | en | |||||||||||
| 書誌情報 |
en : International Symposium on Imaging, Sensing and Optical Memory (ISOM '24) Technical Digest p. Tu-E-13, 発行日 2024-10 |
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| 出版社 | ||||||||||||
| 出版者 | 日本光学会 | |||||||||||
| 言語 | ja | |||||||||||
| 言語 | ||||||||||||
| 言語 | eng | |||||||||||
| 資源タイプ | ||||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_5794 | |||||||||||
| 資源タイプ | conference paper | |||||||||||
| 出版タイプ | ||||||||||||
| 出版タイプ | AM | |||||||||||
| 出版タイプResource | http://purl.org/coar/version/c_ab4af688f83e57aa | |||||||||||
| 会議記述 | ||||||||||||
| 会議名 | International Symposium on Imaging, Sensing, and Optical Memory 2024, ISOM’24 | |||||||||||
| 言語 | en | |||||||||||
| 開始年 | 2024 | |||||||||||
| 開始月 | 10 | |||||||||||
| 開始日 | 20 | |||||||||||
| 終了年 | 2024 | |||||||||||
| 終了月 | 10 | |||||||||||
| 終了日 | 23 | |||||||||||
| 開催会場 | Arcrea HIMEJI | |||||||||||
| 言語 | en | |||||||||||
| 開催地 | Hyogo | |||||||||||
| 言語 | en | |||||||||||
| 開催国 | JPN | |||||||||||
| 研究者情報 | ||||||||||||
| URL | https://hyokadb02.jimu.kyutech.ac.jp/html/100000508_ja.html | |||||||||||
| 連携ID | ||||||||||||
| 値 | 14650 | |||||||||||
