Spatially-varying microscope calibration from unstructured sparse inputs
2020
We propose a method based on blind deconvolution to calibrate the spatially-varying point spread functions of a coded-aperture microscope system. From easy-to- acquire measurements of unstructured fluorescent beads, we recover a spatially-varying forward model that outperforms prior approaches.
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