Paper
10 April 1996 Parametric blind deconvolution of fluorescence microscopy images: preliminary results
Author Affiliations +
Proceedings Volume 2655, Three-Dimensional Microscopy: Image Acquisition and Processing III; (1996) https://doi.org/10.1117/12.237474
Event: Electronic Imaging: Science and Technology, 1996, San Jose, CA, United States
Abstract
Three-dimensional microscopy by computational deconvolution methods requires accurate knowledge of the point spread function (PSF) that characterizes the microscope. Experimental PSF's can only be measured over small regions about focus because the small objects necessary for PSF measurement are dim. Theoretical computation of the PSF requires accurate knowledge of all the experimental setup parameters. Some parameters may be difficult or impossible to measure. In blind deconvolution, the PSF and the specimen are estimated simultaneously, an under-determined problem with non-unique solutions. Most existing approaches to blind deconvolution rely on enforcing constraints on the specimen function and PSF, sometimes in ad-hoc ways. We derived a parametric blind deconvolution method by assuming that the PSF follows a mathematical expression with unknown parameters. The parameters are then estimated together with the specimen function. Preliminary results presented here show that this algorithm rapidly estimates the correct PSF.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jose-Angel Conchello and Qinrong Yu "Parametric blind deconvolution of fluorescence microscopy images: preliminary results", Proc. SPIE 2655, Three-Dimensional Microscopy: Image Acquisition and Processing III, (10 April 1996); https://doi.org/10.1117/12.237474
Lens.org Logo
CITATIONS
Cited by 10 scholarly publications and 2 patents.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Point spread functions

Expectation maximization algorithms

Deconvolution

Microscopes

Microscopy

3D image processing

Algorithm development

Back to Top