Holographic displays have the promise to be the ultimate 3D display technology, able to account for all visual cues. Recent advances in photonics and electronics gave rise to high-resolution holographic display prototypes, indicating that they may become widely available in the near future. One major challenge in driving those display systems is computational: computer generated holography (CGH) consists of numerically simulating diffraction, which is very computationally intensive. Our goal in this paper is to give a broad overview of the state-of-the-art in CGH. We make a classification of modern CGH algorithms, we describe different algorithmic CGH acceleration techniques, discuss the latest dedicated hardware solutions and indicate how to evaluate the perceptual quality of CGH. We summarize our findings, discuss remaining challenges and make projections on the future of CGH.
Blinder, D, Birnbaum, T, Ito, T & Shimobaba, T 2022, 'The state-of-the-art in computer generated holography for 3D display', Light: Advanced Manufacturing, vol. 3, no. 3, 35, pp. 572-600. https://doi.org/10.37188/lam.2022.035
Blinder, D., Birnbaum, T., Ito, T., & Shimobaba, T. (2022). The state-of-the-art in computer generated holography for 3D display. Light: Advanced Manufacturing, 3(3), 572-600. Article 35. https://doi.org/10.37188/lam.2022.035
@article{1ebf4f5b04ea414b933db1768de1d20f,
title = "The state-of-the-art in computer generated holography for 3D display",
abstract = "Holographic displays have the promise to be the ultimate 3D display technology, able to account for all visual cues. Recent advances in photonics and electronics gave rise to high-resolution holographic display prototypes, indicating that they may become widely available in the near future. One major challenge in driving those display systems is computational: computer generated holography (CGH) consists of numerically simulating diffraction, which is very computationally intensive. Our goal in this paper is to give a broad overview of the state-of-the-art in CGH. We make a classification of modern CGH algorithms, we describe different algorithmic CGH acceleration techniques, discuss the latest dedicated hardware solutions and indicate how to evaluate the perceptual quality of CGH. We summarize our findings, discuss remaining challenges and make projections on the future of CGH.",
author = "David Blinder and Tobias Birnbaum and Tomoyoshi Ito and Tomoyoshi Shimobaba",
note = "Funding Information: This research was funded by the Research Foundation - Flanders (FWO), Junior postdoctoral fellowship (12ZQ220N), the joint JSPS-FWO scientific cooperation program (VS07820N) and the Japan Society for the Promotion of Science (19H04132 and JPJSBP120202302). We would like to thank Ayyoub Ahar for advising us on visual quality assessment. Publisher Copyright: {\textcopyright} The Author(s) 2022. Copyright: Copyright 2023 Elsevier B.V., All rights reserved.",
year = "2022",
month = jun,
day = "10",
doi = "10.37188/lam.2022.035",
language = "English",
volume = "3",
pages = "572--600",
journal = "Light: Advanced Manufacturing",
issn = "2689-9620",
number = "3",
}