Supplementary software and data: Bayesian multi-exposure image fusion for robust high dynamic range ptychography

Kodgirwar, Shantanu; Loetgering, Lars; Liu, Chang; Joseph, Aleena; Molina, Daniel S. Penagos; Eschen, Wilhelm; Rothhardt, Jan; Habeck, Michael

doi:10.5281/zenodo.10809893

Published March 12, 2024 | Version v0.1.3

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Supplementary software and data: Bayesian multi-exposure image fusion for robust high dynamic range ptychography

Kodgirwar, Shantanu (Contact person)¹
Loetgering, Lars (Researcher)²
Liu, Chang (Researcher)¹
Joseph, Aleena (Researcher)¹
Molina, Daniel S. Penagos (Researcher)¹
Eschen, Wilhelm (Researcher)¹
Rothhardt, Jan (Supervisor)¹
Habeck, Michael (Supervisor)¹

1. Friedrich Schiller University Jena
2. Carl Zeiss (Germany)

Accompanying software package and data for the publication titled "Bayesian multi-exposure image fusion for robust high dynamic range ptychography". For more info on the installation of dependencies and it's usage visit the below github URL.

Github URL: https://github.com/microscopic-image-analysis/bayes-mef

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bayes-mef.zip

Files (19.6 GB)

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bayes-mef.zip md5:bbd2a7f19e47ab5128942a5a58593e72	19.6 GB	Preview Download

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Programming language: Python

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Created: March 13, 2024
Modified: March 21, 2024

Supplementary software and data: Bayesian multi-exposure image fusion for robust high dynamic range ptychography

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Files

bayes-mef.zip

Files (19.6 GB)

Additional details

Software