Project description:
Super resolution fluorescence microscopy techniques are an ensemble of light-microscopy techniques which achieve spatial resolution beyond the limitations imposed by the diffraction of light. On the other hand, since its introduction in 1983, deconvolution microscopy has become a key processing tool for the visualization of cellular structures of fixed and living specimens in three dimensions and at sub-resolution scale.
Deconvolution is also referred to as an inverse problem, since given the output of the system we aim at recovering the input to the system.
In the proposed project we will extend deconvolution techniques to image de-blurring in microscopy. We will exploit the sparsity prior in acquired images to improve the results.