Blind Deconvolution of Anisoplanatic Aberrations

A computational correction of microscopic images

Master thesis (2019)

Authors

W. van de Ketterij Mechanical Engineering

Contributors

M.H.G. Verhaegen Team Raf Van de Plas - Mechanical, Maritime and Materials Engineering (supervisor 1)
O.A. Soloviev Team Raf Van de Plas - Mechanical, Maritime and Materials Engineering (supervisor 2)
E. Steur Team Bart De Schutter - Mechanical, Maritime and Materials Engineering (supervisor 2)
Faculty
Mechanical Engineering
Copyright: © 2019 wouter van de Ketterij
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Published Date

08-07-2019

Language

English

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Faculty

Mechanical Engineering

Abstract

Correction techniques, such as tangential iterative projections (TIP), were developed to reconstruct the image for the whole field of view. However, due to the three dimensional nature of biological tissues, induced aberrations are different throughout the field of view. This Master of Science thesis shows the development of four algorithms. These algorithms apply TIP to deconvolve images locally. Thereafter, the local results are combined in order to restore images from anisoplanatic aberrations. The difference between the the algorithms developed during this research is the complexity in the spatial domain and in the Fourier domain. It was found that adaptive limited support in the spatial domain increases the im- age quality of the estimated object. A novel approach for multi-frame deconvolution in the Fourier domain has shown to be a promising modification. The use of weighted multi-frame deconvolution in the Fourier domain has lead to improved image quality.

Files

MScThesis.pdf
(.pdf | 9.64 Mb)