Learned Block Iterative Shrinkage Thresholding Algorithm for Photothermal Super Resolution Imaging

Block-sparse regularization is already well known in active thermal imaging and is used for multiple-measurement-based inverse problems. The main bottleneck of this method is the choice of regularization parameters which differs for each experiment. We show the benefits of using a learned block iter...

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Detalles Bibliográficos
Autores principales: Hauffen, Jan Christian, Kästner, Linh, Ahmadi, Samim, Jung, Peter, Caire, Giuseppe, Ziegler, Mathias
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9330715/
https://www.ncbi.nlm.nih.gov/pubmed/35898038
http://dx.doi.org/10.3390/s22155533

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9330715/
https://www.ncbi.nlm.nih.gov/pubmed/35898038
http://dx.doi.org/10.3390/s22155533

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