Blind Deconvolution of Anisoplanatic Aberrations

Blind Deconvolution of Anisoplanatic Aberrations: A computational correction of microscopic images

van de Ketterij, wouter (TU Delft Mechanical, Maritime and Materials Engineering; TU Delft Systems and Control)

Verhaegen, Michel (mentor)
Soloviev, Oleg (graduation committee)
Steur, Erik (graduation committee)

Delft University of Technology

Mechanical Engineering | Systems and Control

2019-07-08

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.

Blind Multi-Frame Deconvolution
Anisoplanatic
Phase Aberrations
Microscopic Images
Weighted Multi-Frame Deconvolution
Computational Correction

http://resolver.tudelft.nl/uuid:daec7fd3-ec35-471b-958d-3152a784e331

Student theses

master thesis

© 2019 wouter van de Ketterij