Gradient-based and wavelet-based compressed sensing approaches for highly undersampled tomographic datasets - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Journal Articles Ultramicroscopy Year : 2021

Gradient-based and wavelet-based compressed sensing approaches for highly undersampled tomographic datasets

Fichier principal
Vignette du fichier
S0304399121000772.pdf (1.51 Mo) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-03366105 , version 1 (09-05-2023)

Licence

Attribution - NonCommercial

Identifiers

Cite

Martin Jacob, Loubna El Gueddari, Jyh-Miin Lin, Gabriele Navarro, Audrey Jannaud, et al.. Gradient-based and wavelet-based compressed sensing approaches for highly undersampled tomographic datasets. Ultramicroscopy, 2021, 225, pp.113289. ⟨10.1016/j.ultramic.2021.113289⟩. ⟨hal-03366105⟩
31 View
38 Download

Altmetric

Share

Gmail Facebook X LinkedIn More