Ptychnet: CNN based fourier ptychography

Armin Kappeler, Sushobhan Ghosh, Jason Holloway, Oliver Strides Cossairt, Aggelos K Katsaggelos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Scopus citations

Abstract

Fourier ptychography is an imaging technique that overcomes the diffraction limit of conventional cameras with applications in microscopy and long range imaging. Diffraction blur causes resolution loss in both cases. In Fourier ptychography, a coherent light source illuminates an object, which is then imaged from multiple viewpoints. The reconstruction of the object from these set of recordings can be obtained by an iterative phase retrieval algorithm. However, the retrieval process is slow and does not work well under certain conditions. In this paper, we propose a new reconstruction algorithm that is based on convolutional neural networks and demonstrate its advantages in terms of speed and performance.

Original languageEnglish (US)
Title of host publication2017 IEEE International Conference on Image Processing, ICIP 2017 - Proceedings
PublisherIEEE Computer Society
Pages1712-1716
Number of pages5
ISBN (Electronic)9781509021758
DOIs
StatePublished - Feb 20 2018
Event24th IEEE International Conference on Image Processing, ICIP 2017 - Beijing, China
Duration: Sep 17 2017Sep 20 2017

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume2017-September
ISSN (Print)1522-4880

Other

Other24th IEEE International Conference on Image Processing, ICIP 2017
CountryChina
CityBeijing
Period9/17/179/20/17

    Fingerprint

Keywords

  • CNN
  • Convolutional Neural Network
  • Fourier ptychography

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

Cite this

Kappeler, A., Ghosh, S., Holloway, J., Cossairt, O. S., & Katsaggelos, A. K. (2018). Ptychnet: CNN based fourier ptychography. In 2017 IEEE International Conference on Image Processing, ICIP 2017 - Proceedings (pp. 1712-1716). (Proceedings - International Conference on Image Processing, ICIP; Vol. 2017-September). IEEE Computer Society. https://doi.org/10.1109/ICIP.2017.8296574