Abstract

As for the confocal laser scanning microscope (CLSM) imaging system, the collected weak fluorescence signals are always distorted by optic blur and severe photon-counting noise, and the deconvolution for CLSM images is a typical ill-posed inverse problem, which is highly sensitive to the measurement noise. To promote the reconstruction quality for characteristics of low intensity and strong noise, we employed the prominent total variation regularization (TV) to enforce the sparsity of a fluorescent image gradient with rich details. However, the well-known reconstruction artifacts (e.g., artificial staircase) emerge with TV prior. To settle this issue, we utilized a robust first-order discretization yielding near-isotropy with a gradient field to depress the reconstruction artifacts. Furthermore, the bound constraint was suited to restrain final reconstruction results from appearing unreasonably explosive. For the proposed optimization minimizer with linear constraint, we take one proximal gradient for approximate estimation of each subproblem under the framework of the inexact alternating direction method of multipliers. Moreover, we incorporated a Nesterov’s scheme into the numerical method for acceleration of iteration updating. Compared with other competing methods, both the simulation and practical results demonstrate the effectiveness of our proposed model for CLSM image deconvolution.

© 2019 Optical Society of America

Full Article  |  PDF Article
OSA Recommended Articles
Hybrid high-order nonlocal gradient sparsity regularization for Poisson image deconvolution

Tao He, Jie Hu, and Haiqing Huang
Appl. Opt. 57(35) 10243-10256 (2018)

Total variation regularized deconvolution for extended depth of field microscopy

Ramzi N. Zahreddine and Carol J. Cogswell
Appl. Opt. 54(9) 2244-2254 (2015)

Blind deconvolution for thin-layered confocal imaging

Praveen Pankajakshan, Bo Zhang, Laure Blanc-Féraud, Zvi Kam, Jean-Christophe Olivo-Marin, and Josiane Zerubia
Appl. Opt. 48(22) 4437-4448 (2009)

References

You do not have subscription access to this journal. Citation lists with outbound citation links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Figures (14)

You do not have subscription access to this journal. Figure files are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Tables (3)

You do not have subscription access to this journal. Article tables are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Equations (31)

You do not have subscription access to this journal. Equations are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription