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.

Published in:
2008 Ieee International Symposium On Biomedical Imaging: From Nano To Macro, Vols 1-4, 157-160
Presented at:
5th IEEE International Symposium on Biomedical Imaging - From Nano to Macro, Paris, FRANCE, May 14-17, 2008
Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa

 Record created 2010-11-30, last modified 2018-03-18

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