IEEE Workshop on Signal Processing Systems (SIPS), San Francisco, USA 2010
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.