Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Parametric blind deconvolution: a robust method for the simultaneous estimation of image and blur.

J Markham1, J A Conchello

  • 1Institute for Biomedical Computing, Washington University, St. Louis, Missouri 63110, USA.

Journal of the Optical Society of America. A, Optics, Image Science, and Vision
|October 12, 1999
PubMed
Summary

This study introduces a new maximum-likelihood method for blind deconvolution microscopy. It accurately estimates the microscope's point-spread function (PSF) and removes blur, even with image noise and aberrations.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

The use of aspirin for primary and secondary prevention in venous thromboembolism and other cardiovascular disorders.

Thrombosis research·2014
Same author

Automated and semi-automated cell tracking: addressing portability challenges.

Journal of microscopy·2011
Same author

Occupational chest problems.

Canadian family physician Medecin de famille canadien·2011
Same author

Occupational medicine: new interface for family medicine?

Canadian family physician Medecin de famille canadien·2011
Same author

Enhanced three-dimensional reconstruction from confocal scanning microscope images. II. Depth discrimination versus signal-to-noise ratio in partially confocal images.

Applied optics·2010
Same author

Theoretical analysis of a rotating-disk partially confocal scanning microscope.

Applied optics·2010

Area of Science:

  • Microscopy
  • Image Processing
  • Computational Imaging

Background:

  • Blind deconvolution in microscopy is an ill-posed problem.
  • Existing methods often rely on restrictive constraints for the specimen and point-spread function (PSF).

Purpose of the Study:

  • To develop a robust blind deconvolution method using a parameterized PSF model.
  • To simultaneously estimate the specimen and PSF while ensuring nonnegativity and satisfying PSF constraints.

Main Methods:

  • Developed a maximum-likelihood-based blind deconvolution algorithm.
  • Assumed a mathematical model for the PSF dependent on a small number of parameters.
  • Estimated unknown PSF parameters and the specimen function concurrently.

Main Results:

Related Experiment Videos

  • Successfully estimated the point-spread function (PSF) and removed out-of-focus blur.
  • The method demonstrated robustness against PSF aberrations and image noise.
  • Ensured specimen nonnegativity through the maximum-likelihood approach.

Conclusions:

  • The proposed method offers a robust solution for blind deconvolution in microscopy.
  • It effectively addresses the underdetermined nature of the problem by utilizing a parameterized PSF model.
  • Enables accurate image restoration and PSF estimation in challenging imaging conditions.