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Proceedings Paper

Nonlinear image restoration methods for marker extraction in 3D fluorescent microscopy
Author(s): Aleh Kryvanos; Juergen Hesser; Gabriele Steidl
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Paper Abstract

Localization of biological markers in images obtained by fluorescent microscopy is a relevant problem in biological research. Due to blurring from imaging and noise, the analysis of supra-molecular structures can be improved by image restoration. In this paper, we compare various deblurring algorithms with and without regularization. In the first group we consider the EM (Expectation Maximization) and the JVC (Jansson-van-Cittert) algorithms and examine the effect of the Tikhonov and the TV (Total Variation) regularization in the second group. The last approach uses the I-divergence as similarity measure. As solution method for our new I-divergence--TV model we propose a non-linear projective conjugate gradient algorithm with inexact linear search. Optimal regularization parameters were found by the shape analysis of corresponding L-curves.

Paper Details

Date Published: 11 March 2005
PDF: 12 pages
Proc. SPIE 5674, Computational Imaging III, (11 March 2005); doi: 10.1117/12.586909
Show Author Affiliations
Aleh Kryvanos, Institute for Computational Medicine, Univ. Mannheim and Univ. Heidelberg (Germany)
Juergen Hesser, Institute for Computational Medicine, Univ. Mannheim and Univ. Heidelberg (Germany)
Gabriele Steidl, Univ. Mannheim (Germany)


Published in SPIE Proceedings Vol. 5674:
Computational Imaging III
Charles A. Bouman; Eric L. Miller, Editor(s)

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