Super-resolution and point spread function sensitivity analysis of the expectation-maximization algorithm for computational optical sectioning microscopy

Jose-Angel Conchello

doi:10.1117/12.188056

30 September 1994 Super-resolution and point spread function sensitivity analysis of the expectation-maximization algorithm for computational optical sectioning microscopy

Jose-Angel Conchello

Author Affiliations +

Proceedings Volume 2302, Image Reconstruction and Restoration; (1994) https://doi.org/10.1117/12.188056
Event: SPIE's 1994 International Symposium on Optics, Imaging, and Instrumentation, 1994, San Diego, CA, United States

Abstract

Computational optical sectioning microscopy with a non-confocal microscope is fundamentally limited because the optical transfer function (OTF), the Fourier transform of the point spread function (PSF) is exactly zero over a conic region of the spatial frequency domain. Because of this missing cone of optical information, images are potentially artifactual. To over come this limitation superresolution, in the sense of band extrapolation, is necessary. We present an analysis of how the expectation maximization algorithm for maximum likelihood image estimation achieves this superresolution. We also present experimental results showing this superresolving capability. In practice this capability is often compromised because the PSF has to be truncated to a limited spatial support for algorithm implementation. Therefore we also present an analysis of the sensitivity of superresolution to truncation of the PSF to a finite extent.

Citation Download Citation

Jose-Angel Conchello "Super-resolution and point spread function sensitivity analysis of the expectation-maximization algorithm for computational optical sectioning microscopy", Proc. SPIE 2302, Image Reconstruction and Restoration, (30 September 1994); https://doi.org/10.1117/12.188056

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