# COL0RME: COvariance-based $\ell_0$ super-Resolution Microscopy with intensity Estimation

1 MORPHEME - Morphologie et Images
CRISAM - Inria Sophia Antipolis - Méditerranée , IBV - Institut de Biologie Valrose : U1091, Laboratoire I3S - SIS - Signal, Images et Systèmes
2 IRIT-SC - Signal et Communications
IRIT - Institut de recherche en informatique de Toulouse
Abstract : Super-resolution light microscopy overcomes the physical barriers due to light diffraction, allowing for the observation of otherwise indistinguishable subcellular entities. However, the specific acquisition conditions required by state-of-the-art super-resolution methods to achieve adequate spatio-temporal resolution are often very challenging. Exploiting molecules fluctuations allows good spatio-temporal resolution live-cell imaging by means of common microscopes and conventional fluorescent dyes. In this work, we present the method COL0RME for COvariance-based $\ell_0$ super-Resolution Microscopy with intensity Estimation. It codifies the assumption of sparse distribution of the fluorescent molecules as well as the temporal and spatial independence between emitters via a non-convex optimization problem formulated in the covariance domain. In order to deal with real data, the proposed approach also estimates background and noise statistics. It also includes a final estimation step where intensity information is retrieved, which is valuable for biological interpretation and future applications to super-resolution imaging.
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Conference papers
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https://hal.archives-ouvertes.fr/hal-02979332
Contributor : Vasiliki Stergiopoulou Connect in order to contact the contributor
Submitted on : Monday, November 29, 2021 - 10:31:39 PM
Last modification on : Friday, January 21, 2022 - 3:13:21 AM

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### Citation

Vasiliki Stergiopoulou, José Henrique de M Goulart, Sébastien Schaub, Luca Calatroni, Laure Blanc-Féraud. COL0RME: COvariance-based $\ell_0$ super-Resolution Microscopy with intensity Estimation. IEEE 18th International Symposium on Biomedical Imaging (ISBI 2021), Apr 2021, Nice (Virtual), France. pp.349-352, ⟨10.1109/ISBI48211.2021.9433976⟩. ⟨hal-02979332⟩

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