Randomness assisted in-line holography with deep learning
We propose and demonstrate a holographic imaging scheme exploiting random
illuminations for recording hologram and then applying numerical reconstruction and twin …
illuminations for recording hologram and then applying numerical reconstruction and twin …
Deep DIH: single-shot digital in-line holography reconstruction by deep learning
Digital in-line holography (DIH) is broadly used to reconstruct 3D shapes of microscopic
objects from their 2D holograms. One of the technical challenges in the reconstruction stage …
objects from their 2D holograms. One of the technical challenges in the reconstruction stage …
eHoloNet: a learning-based end-to-end approach for in-line digital holographic reconstruction
It is well known that in-line digital holography (DH) makes use of the full pixel count in
forming the holographic imaging. But it usually requires phase-shifting or phase retrieval …
forming the holographic imaging. But it usually requires phase-shifting or phase retrieval …
Three-dimensional deeply generated holography
R Horisaki, Y Nishizaki, K Kitaguchi, M Saito… - Applied optics, 2021 - opg.optica.org
In this paper, we present a noniterative method for 3D computer-generated holography
based on deep learning. A convolutional neural network is adapted for directly generating a …
based on deep learning. A convolutional neural network is adapted for directly generating a …
End-to-end learning for digital hologram reconstruction
Digital holography is a well-known method to perform three-dimensional imaging by
recording the light wavefront information originating from the object. Not only the intensity …
recording the light wavefront information originating from the object. Not only the intensity …
High-speed computer-generated holography using convolutional neural networks
High-Speed Computer-Generated Holography Using Convolutional Neural Networks Page 1
BTu2C.2.pdf Biophotonics Congress: Biomedical Optics 2020 (Translational, Microscopy, OCT …
BTu2C.2.pdf Biophotonics Congress: Biomedical Optics 2020 (Translational, Microscopy, OCT …
Lensless computational imaging with a hybrid framework of holographic propagation and deep learning
Z Tian, Z Ming, A Qi, F Li, X Yu, Y Song - Optics Letters, 2022 - opg.optica.org
Lensless imaging has attracted attention as it avoids the bulky optical lens. Lensless
holographic imaging is a type of a lensless imaging technique. Recently, deep learning has …
holographic imaging is a type of a lensless imaging technique. Recently, deep learning has …
Comprehensive deep learning model for 3D color holography
A Yolalmaz, E Yüce - Scientific reports, 2022 - nature.com
Holography is a vital tool used in various applications from microscopy, solar energy,
imaging, display to information encryption. Generation of a holographic image and …
imaging, display to information encryption. Generation of a holographic image and …
Deep learning-based holographic reconstruction in digital holography
Deep learning-based holographic reconstruction in digital holography Page 1 HTu4B.2.pdf OSA
Imaging and Applied Optics Congress 2020 (3D, AOMS, COSI, DH, ISA) © OSA 2020 Deep …
Imaging and Applied Optics Congress 2020 (3D, AOMS, COSI, DH, ISA) © OSA 2020 Deep …
Deep-learning based reconstruction in optical scanning holography
X Zhuang, A Yan, PWM Tsang, TC Poon - Optics and Lasers in …, 2022 - Elsevier
Optical scanning holography (OSH) can be used to record holograms of large three-
dimensional (3-D) objects, based on a two-dimensional (2-D) optical scan. For semi …
dimensional (3-D) objects, based on a two-dimensional (2-D) optical scan. For semi …