Abstract
A recently developed algorithm is applied to calculate a state space realization of a 3D microscopy image set. It is based on interpreting the image set as the impulse response of a 3D separable system. As an application it is shown how this algorithm, combined with approximation steps, can be used to suppress noise in 3D experimental point spread functions. The approach was motivated by a well known problem that a noisy point spread function degrades the results of deconvolution algorithms for the restoration of 3D fluorescence microscopy image sets. The proposed approach can also be applied to 3D fluorescence microscopy image sets of cells.
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