Hostname: page-component-586b7cd67f-tf8b9 Total loading time: 0 Render date: 2024-11-26T18:36:12.378Z Has data issue: false hasContentIssue false
  • English
  • Français

Denoising of Sparse Three- and Four-dimensional Hyperspectral Electron Microscopy Data Using a Total Variational Method

Published online by Cambridge University Press:  30 July 2020

Steven Zeltmann ,
Andrew Minor  and
Colin Ophus
Steven Zeltmann
Affiliation:
University of California-Berkeley, Berkeley, California, United States
Andrew Minor
Affiliation:
University of California-Berkeley, Berkeley, California, United States Lawrence Berkeley National Laboratory, Berkeley, California, United States
Colin Ophus
Affiliation:

Abstract

An abstract is not available for this content so a preview has been provided. As you have access to this content, a full PDF is available via the ‘Save PDF’ action button.
Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Advances in Modeling, Simulation, and Artificial Intelligence in Microscopy and Microanalysis for Physical and Biological Systems
Information
Microscopy and Microanalysis , Volume 26 , Supplement S2 , August 2020 , pp. 1724 - 1726
Check for updates
Copyright
Copyright © Microscopy Society of America 2020

References

Ciston, et al. , Microscopy and Microanalysis (2019) 25(S2): pp.1930-193110.1017/S1431927619010389CrossRefGoogle Scholar
Dabov, et al. , Proc SPIE (2006) 606414Google Scholar
Batson, and Royer, , arXiv:1901.11365 [cs.CV]Google Scholar
Jia, and Zhou, , Avd. Comput. Math (2010) 33:231-24110.1007/s10444-009-9128-5CrossRefGoogle Scholar