Title
Off-The-Grid Covariance-Based Super-Resolution Fluctuation Microscopy
Abstract
Super-resolution fluorescence microscopy overcomes blurring arising from light diffraction, allowing the reconstruction of fine scale details in biological structures. Standard methods come at the expense of long acquisition time and/or harmful effects on the biological sample, which makes the problem quite challenging for the imaging of body cells. A promising new avenue is the exploitation of molecules fluctuations, allowing live-cell imaging with good spatio-temporal resolution through common microscopes and conventional fluorescent dyes. Several numerical algorithms have been developed in the literature and used for fluctuant time series. These techniques are developed within the discrete setting, namely the super-resolved image is defined on a finer grid than the observed images. On the contrary, gridless optimisation does not rely on a fine grid and is rather an optimisation of Dirac measures in number, amplitudes and positions. In this work, we present an off-the-grid problem accounting for the independence of fluctuations.
Year
DOI
Venue
2022
10.1109/ICASSP43922.2022.9746845
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Bastien Laville100.34
Laure Blanc-Feraud25916.71
Gilles Aubert31275108.17