Compressed sensing applications for biological microscopy

This paper provides an overview of some compressed sensing contributions to biological microscopy developed in our laboratory. They are mainly on four topics: (i) a CS-based denoising framework exploiting a Total Variation sparsity prior and very limited number of measurements in the Fourier domain, (ii) practical experiments on fluorescence image data demonstrating that thanks to CS the signal-to-noise ratio can be improved while still reducing the photobleaching effect, (iii) a CS reconstruction framework combining Fourier magnitude measurements and Fourier phase estimation for sequential microscopy image acquisition, (iv) a microscopy acquisition scheme successfully combining Compressed Sensing (CS) and digital holography.