ADMM-TGV deconvolution algorithm for STEM-EELS maps

Deconvolution algorithm for 3D STEM-EELS maps
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Actualizado 15 jun 2025

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Deconvolution algorithm for 3D STEM-EELS maps with total generalized variation (TGV), non-negativity prior and residual balancing for automated and unbiased parameter choice. The algorithm employs a noise model for scintillation-based CCD detectors, as they are often used in EELS, and considers the binning of the detector to create spectra as well as noise correlations occurring on such detectors.
A detailled derivation and description of the algorithm is provided in:
Christian Zietlow and Jörg K. N. Lindner
An unbiased ADMM-TGV algorithm for the deconvolution of STEM-EELS maps
Ultramicroscopy (2025), Article 114159
https://doi.org/10.1016/j.ultramic.2025.114159

Citar como

Christian Zietlow (2026). ADMM-TGV deconvolution algorithm for STEM-EELS maps (https://la.mathworks.com/matlabcentral/fileexchange/181166-admm-tgv-deconvolution-algorithm-for-stem-eels-maps), MATLAB Central File Exchange. Recuperado .

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Se creó con R2021a
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Versión Publicado Notas de la versión
1.0.5

added logo

1.0.4

.

1.0.3

- gpu script of the deconvolution algorithm
- fixed description of variable Phi: shited -> shifted

1.0.2

updated paper details

1.0.1

title updated

1.0.0