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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

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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
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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