Deep learning-based incoherent holographic camera enabling acquisition of real-world holograms for holographic streaming system

While recent research has shown that holographic displays can represent photorealistic 3D holograms in real time, the difficulty in acquiring high-quality real-world holograms has limited the realization of holographic streaming systems. Incoherent holographic cameras, which record holograms under d...

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Bibliographic Details
Published in:Nature communications 2023-06, Vol.14 (1), p.3534-3534, Article 3534
Main Authors: Yu, Hyeonseung, Kim, Youngrok, Yang, Daeho, Seo, Wontaek, Kim, Yunhee, Hong, Jong-Young, Song, Hoon, Sung, Geeyoung, Sung, Younghun, Min, Sung-Wook, Lee, Hong-Seok
Format: Article
Language:English
Subjects:
639/624/1075/146
639/624/1107/510
639/766/930/2735
Cameras
Deep learning
Filters
Holograms
Holography
Humanities and Social Sciences
Lasers
multidisciplinary
Neural networks
Real time
Science
Science (multidisciplinary)
Streaming
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Summary:While recent research has shown that holographic displays can represent photorealistic 3D holograms in real time, the difficulty in acquiring high-quality real-world holograms has limited the realization of holographic streaming systems. Incoherent holographic cameras, which record holograms under daylight conditions, are suitable candidates for real-world acquisition, as they prevent the safety issues associated with the use of lasers; however, these cameras are hindered by severe noise due to the optical imperfections of such systems. In this work, we develop a deep learning-based incoherent holographic camera system that can deliver visually enhanced holograms in real time. A neural network filters the noise in the captured holograms, maintaining a complex-valued hologram format throughout the whole process. Enabled by the computational efficiency of the proposed filtering strategy, we demonstrate a holographic streaming system integrating a holographic camera and holographic display, with the aim of developing the ultimate holographic ecosystem of the future. The authors develop a deep learning-based incoherent holographic camera system in order to deliver visually enhanced holograms in real-time. The neural network filters the noise in the captured holograms, and by integrating a holographic camera and a display, they demonstrate a holographic streaming system.
ISSN:2041-1723
2041-1723
DOI:10.1038/s41467-023-39329-0