An accurate PSF model with few parameters for axially shift-variant deconvolution

Accurate knowledge of an imaging system´s point spread function (PSF) is crucial for successful deconvolution. For fluorescence microscopy, PSF estimations based on either theoretical models or experimental measurements are available. However, due to the axially shift-variant nature of the PSF, neither method guarantees an estimate that is valid for the entire object space. In this work, we present a reduced- parameter version of a state-of-the-art theoretical model. We give a maximum-likelihood based algorithm for the estimation of its parameters, and we show how a fit of our model to two axially isolated point source measurements in an experimental setup can be used to accurately reproduce measured PSFs within the entire specimen.