Electronic Theses and Dissertations

Identifier

951

Date

2013

Document Type

Thesis

Degree Name

Master of Science

Major

Electrical and Computer Engr

Concentration

Computer Engineering

Committee Chair

Chrysanthe Preza

Committee Member

Eddie Jacobs

Committee Member

Aaron L Robinson

Abstract

In three-dimensional fluorescence microscopy, the image formation process is inherently depth variant (DV) due to the refractive index mismatch between imaging layers, which causes depth-induced spherical aberration (SA). In this study, we present a quantitative comparison among different image restoration techniques developed based on a DV imaging model for microscopy in order to assess their ability to correct SA and their impact on restoration. The imaging models approximate DV imaging by either stratifying the object space or image space. For the reconstruction purpose, we used regularized DV algorithms with object stratification method such as the Expectation Maximization (EM), Conjugate Gradient; Principal Component Analysis based expectation maximization (PCA-EM), and Inverse filtering (IF). Reconstructions from simulated data and measured data show that better restoration results are achieved with the DV PCA-EM method than the other DV algorithms in terms of execution time and restoration quality of the image.

Comments

Data is provided by the student.

Library Comment

Dissertation or thesis originally submitted to the local University of Memphis Electronic Theses & dissertation (ETD) Repository.

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