Abstract
We are interested in blind restoration of 3D confocal microscopy images. One challenging problem in this system is the depth-variant (DV) blur due to refractive index mismatch. In our work, we simplify the problem by approximating the DV point spread function (PSF) by a convex combination of a set of space-invariant (SI) PSFs. We show that each SI PSF can be approximated by a Gaussian function given by few parameters. One advantage of such an approximation is that positivity and normalization of the PSF are naturally ensured. The problem is thus reduced to the estimation of the object and the PSF parameters. We design a new criterion allowing both estimations of the object and the DV PSF, with physical constraints included. The method is validated on simulated and real confocal microscopy data.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
