Accurate 3D PSF estimation from a wide-field microscopy image

The 3D point-spread function (PSF) plays a fundamental role in wide-field fluorescence microscopy. An accurate PSF estimation can significantly improve the performance of deconvolution algorithms. In this work, we propose a calibration-free method to obtain the PSF directly from the image obtained. Specifically, we first parametrize the spherically aberrated PSF as a linear combination of few basis functions. The coefficients of these basis functions are then obtained iteratively by minimizing a novel criterion, which is derived from the mixed Poisson-Gaussian noise statistics. Experiments demonstrate that the proposed approach results in highly accurate PSF estimations.