Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Deep-learning Accelerated Fringe Pattern Filtration Using Variational Image Decomposition

Not Accessible

Your library or personal account may give you access

Abstract

Using a deep convolutional neural network we accelerated our unsupervised variational image decomposition algorithm making it not only automatic, robust and accurate but also fast. Reduction of computation time is nearly 90%.

© 2020 The Author(s)

PDF Article  |   Presentation Video
More Like This
Deep learning aided Variational Hilbert Quantitative Phase Imaging

Maria Cywińska, Krzysztof Patorski, and Maciej Trusiak
HTu3C.3 Digital Holography and Three-Dimensional Imaging (DH) 2023

Snap-shot fringe pattern enhancement using period-guided bidimensional empirical mode decomposition

Paweł Gocłowski and Maciej Trusiak
FTh2A.4 Frontiers in Optics (FiO) 2020

Noise influence on DeepDensity: convolutional neural network for local fringe density map estimation

Maria Cywińska, Filip Brzeski, Wiktor Krajnik, Krzysztof Patorski, and Maciej Trusiak
DTh1D.5 Digital Holography and Three-Dimensional Imaging (DH) 2021

Presentation Video

Presentation video access is available to:

  1. Optica Publishing Group subscribers
  2. Technical meeting attendees
  3. Optica members who wish to use one of their free downloads. Please download the article first. After downloading, please refresh this page.

Contact your librarian or system administrator
or
Log in to access Optica Member Subscription or free downloads


More Like This
Deep learning aided Variational Hilbert Quantitative Phase Imaging

Maria Cywińska, Krzysztof Patorski, and Maciej Trusiak
HTu3C.3 Digital Holography and Three-Dimensional Imaging (DH) 2023

Snap-shot fringe pattern enhancement using period-guided bidimensional empirical mode decomposition

Paweł Gocłowski and Maciej Trusiak
FTh2A.4 Frontiers in Optics (FiO) 2020

Noise influence on DeepDensity: convolutional neural network for local fringe density map estimation

Maria Cywińska, Filip Brzeski, Wiktor Krajnik, Krzysztof Patorski, and Maciej Trusiak
DTh1D.5 Digital Holography and Three-Dimensional Imaging (DH) 2021

Identifying Diabetes in Mice using Optical Coherence Tomography Angiography Images of the Ears and Deep Learning

Martin Pfister, Kornelia Schuetzenberger, Jasmin Schaefer, Hannes Stegmann, Martin Groeschl, and René M. Werkmeister
OM4E.4 Optical Coherence Tomography (OCT) 2020

Randomized Probe Imaging through Deep K-Learning

Zhen Guo, Abraham Levitan, George Barbastathis, and Riccardo Comin
CTh7A.6 Computational Optical Sensing and Imaging (COSI) 2021

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.