Sparse deconvolution: one decisive step into computational fluorescence superresolution
We stumble upon an iterative optimization of fluorescence images followed by the RL deconvolution using the spatiotemporal continuity and sparsity prior knowledge. This Sparse deconvolution algorithm can extend spatial resolutions of fluorescence microscopes beyond their hardware constraints.
