Abstract

We describe a technique for incorporating convolutional-neural-network models into a comprehensive approach for coherent-image reconstruction in the presence of noise and phase errors using the consensus equilibrium framework.

© 2019 The Author(s)

PDF Article
More Like This
Non-Iterative Holographic Image Reconstruction and Phase Retrieval Using a Deep Convolutional Neural Network

Yair Rivenson, Yibo Zhang, Harun Günaydın, Da Teng, and Aydogan Ozcan
STh1J.3 CLEO: Science and Innovations (CLEO_SI) 2018

Digital hologram reconstruction segmentation using a convolutional neural network

Tomi Pitkäaho, Aki Manninen, and Thomas J. Naughton
Th3A.1 Digital Holography and Three-Dimensional Imaging (DH) 2019

Analysis of 3D Image Reconstruction for Spherical Object Using Convolutional Neural Network in Digital Holography

Wooyoung Jeong, Kyungchan Son, Wonseok Jeon, and Hyunseok Yang
JTu4A.24 3D Image Acquisition and Display: Technology, Perception and Applications (3D) 2018

References

You do not have subscription access to this journal. Citation lists with outbound citation links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription