Poster + Paper
14 March 2023 Fast deep-trained transformation technique for computer-generated holograms
Author Affiliations +
Proceedings Volume 12443, Advances in Display Technologies XIII; 124430H (2023) https://doi.org/10.1117/12.2649721
Event: SPIE OPTO, 2023, San Francisco, California, United States
Conference Poster
Abstract
We present a numerical transformation technique for Computer-Generated Holograms (CGHs) using the deep learning method. Using the proposed technique, one can obtain CGHs for a user-defined holographic display system from given CGHs. The calculation speed of the proposed technique is about 20 times faster than that of the conventional free-space propagation algorithm. We verify through both numerical simulation and optical experiment that focal stacks produced with the CGHs obtained by the proposed technique are similar to those produced with the target CGHs.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Juhyun Lee, Yoonchan Jeong, and Byoungho Lee "Fast deep-trained transformation technique for computer-generated holograms", Proc. SPIE 12443, Advances in Display Technologies XIII, 124430H (14 March 2023); https://doi.org/10.1117/12.2649721
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KEYWORDS
Computer generated holography

Holographic displays

Spatial light modulators

Deep learning

Holograms

Neural networks

Numerical simulations

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