In-line hologram reconstruction with deep learning Page 1 DW2F.2.pdf Imaging and Applied
Optics 2018 (3D, AIO, AO, COSI, DH, IS, LACSEA, LSC, MATH, pcAOP) © OSA 2018 In-line …

Phase imaging for digital holography with deep learning Page 1 Phase imaging for digital
holography with deep learning Chencen Xiong,1 Zhenbo Ren,1,* Jianglei Di,2 and Jianlin Zhao1 …

Digital holography imaging utilizes the special properties of light and photons to capture the
detailed images of microscopic objects, such as organs, tissues, and cells. Usually, phase …

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 …

Non-Iterative Holographic Image Reconstruction and Phase Retrieval Using a Deep
Convolutional Neural Network Page 1 STh1J.3.pdf CLEO 2018 © OSA 2018 Non-Iterative …

Deep learning-based image reconstruction methods have achieved remarkable success in
phase recovery and holographic imaging. However, the generalization of their image …

In-line holography has been widely used in various fields because of its advantages such as
simple optical path, low requirement of light source coherence and low utilization of the …

Current development in a deep neural network (DNN) has given an opportunity to a novel
framework for the reconstruction of a holographic image and a phase recovery method with …

Single-shot reconstruction of the inline hologram is highly desirable as a cost-effective and
portable imaging modality in resource-constrained environments. However, the twin image …

A robust method is proposed to reconstruct images with only one hologram in digital
holography by introducing a deep learning (DL) network. The U-net neural network is …