High-Quality Hologram Generation Based on Advanced Layering Approach and Deep Neural Network for Holographic Display

Tuvshinjargal Amgalan; Erkhembaatar Dashdavaa; F M Fahmid Hossain; Rupali Shinde; Md. Biddut Hossain; Hui-Ying Wu; Seok-Hee Jeon; Nam-Kim

doi:10.1364/3D.2023.JTu4A.30

Optica Imaging Congress (3D, COSI, DH, FLatOptics, IS, pcAOP)
Technical Digest Series (Optica Publishing Group, 2023),
paper JTu4A.30
•https://doi.org/10.1364/3D.2023.JTu4A.30

High-Quality Hologram Generation Based on Advanced Layering Approach and Deep Neural Network for Holographic Display

Tuvshinjargal Amgalan, Erkhembaatar Dashdavaa, F M Fahmid Hossain, Rupali Shinde, Md. Biddut Hossain, Hui-Ying Wu, Seok-Hee Jeon, and Nam-Kim

3D Image Acquisition and Display: Technology, Perception and Applications 2023

Boston, Massachusetts United States
14–17 August 2023
ISBN: 978-1-957171-28-9

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Joint Poster Session I (JTu4A)

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T. Amgalan, E. Dashdavaa, F. M. F. Hossain, R. Shinde, M. B. Hossain, H. Wu, S. Jeon, and Nam-Kim, "High-Quality Hologram Generation Based on Advanced Layering Approach and Deep Neural Network for Holographic Display," in Optica Imaging Congress (3D, COSI, DH, FLatOptics, IS, pcAOP), Technical Digest Series (Optica Publishing Group, 2023), paper JTu4A.30.

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Abstract

We propose generated a high-quality 3D model using a deep neural network by acquiring high-resolution 3D data from real-world objects and generated a high-speed and high-quality 3D CGH based on integrated hybrid map layering for use in holographic display.

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