Compressed sensing in fluorescence microscopy

• Published in: Progress in biophysics and molecular biology Vol. 168; pp. 66 - 80
• Main Authors: Calisesi, Gianmaria, Ghezzi, Alberto, Ancora, Daniele, D'Andrea, Cosimo, Valentini, Gianluca, Farina, Andrea, Bassi, Andrea
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01.01.2022
• Subjects: Algorithms; Animals; Biomedical imaging; Compressed sensing; Computational imaging; Fluorescence microscopy; Inverse problems; Magnetic Resonance Imaging; Microscopy, Fluorescence; Optical Imaging; Signal Processing, Computer-Assisted; Optical imaging; Inverse problems; Computational imaging; Compressed sensing; Fluorescence microscopy; Biomedical imaging

Compressed sensing (CS) is a signal processing approach that solves ill-posed inverse problems, from under-sampled data with respect to the Nyquist criterium. CS exploits sparsity constraints based on the knowledge of prior information, relative to the structure of the object in the spatial or other...