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Conference Paper
Hologram Reconstruction Using Cascaded Deep Learning Networks
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- Authors
- Hyon-Gon Choo, Yeon-Gyeong Ju, Kwan-Jung Oh, Yongjun Lim, Jae-Hyeung Park
- Issue Date
- 2021-07
- Citation
- OSA Imaging and Applied Optics Congress 2021, pp.1-2
- Language
- English
- Type
- Conference Paper
- Abstract
- Deep learning technology is one of the emerging topics in solving problems in all scientific fields. In this paper, we address a hologram reconstruction method using cascaded multitask networks. A cascaded network consists of two U-net networks. The first is used for conversion between hologram plane and image plane and the other is used for extraction of image and depth. To train the network, we simulate an optical holographic microscopy setup. Experimental results show that the proposed approach can restore effectively complex optical fields and depth information.
- KSP Keywords
- Cascaded network, Deep learning network, Depth information, Emerging topics, Hologram reconstruction, Holographic microscopy, Image plane, Learning Technology, Reconstruction method, complex optical fields, deep learning(DL)