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.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.