Removal of unwanted terms from single shot in-line digital holograms by convolutional neural network

Bora Duman; G. Bora Esmer

doi:10.1117/12.3017233

18 June 2024 Removal of unwanted terms from single shot in-line digital holograms by convolutional neural network

Bora Duman, G. Bora Esmer

Proceedings Volume 12996, Unconventional Optical Imaging IV; 129960G (2024) https://doi.org/10.1117/12.3017233
Event: SPIE Photonics Europe, 2024, Strasbourg, France

Abstract

A model to achieve high-resolution three-dimensional microscopic images from synthetically generated digital holograms by using Convolutional Neural Networks (CNNs) is proposed. By employing low-cost microscopy systems and computational techniques, we demonstrate that proposed model provides viable alternative to costly high-resolution microscopic systems. Specifically, the study focuses on the elimination of the unwanted terms in backward-propagated holograms to closely approximate original high-resolution objects.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Bora Duman and G. Bora Esmer "Removal of unwanted terms from single shot in-line digital holograms by convolutional neural network", Proc. SPIE 12996, Unconventional Optical Imaging IV, 129960G (18 June 2024); https://doi.org/10.1117/12.3017233

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