The Iteratively Regularized Gauß-Newton Method with Convex Constraints and Applications in 4Pi-Microscopy

Details The Iteratively Regularized Gauß-Newton Method with Convex Constraints and Applications in 4Pi-Microscopy The Iteratively Regularized Gauß-Newton Method with Convex Constraints and Applications in 4Pi-Microscopy

2011-06-28

arxiv.org/abs/1106.5812v1

Inverse Problems, 28 (2012), 015012

Mathematics

Functional Analysis

Scientific paper

This paper is concerned with the numerical solution of nonlinear ill-posed operator equations involving convex constraints. We study a Newton-type method which consists in applying linear Tikhonov regularization with convex constraints to the Newton equations in each iteration step. Convergence of this iterative regularization method is analyzed if both the operator and the right hand side are given with errors and all error levels tend to zero. Our study has been motivated by the joint estimation of object and phase in 4Pi microscopy, which leads to a semi-blind deconvolution problem with nonnegativity constraints. The performance of the proposed algorithm is illustrated both for simulated and for three-dimensional experimental data.

Affiliated with

Also associated with

No associations

Rating

The Iteratively Regularized Gauß-Newton Method with Convex Constraints and Applications in 4Pi-Microscopy does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with The Iteratively Regularized Gauß-Newton Method with Convex Constraints and Applications in 4Pi-Microscopy, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and The Iteratively Regularized Gauß-Newton Method with Convex Constraints and Applications in 4Pi-Microscopy will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-358678