Stopping rules for iterative methods in nonnegatively constrained deconvolution

We consider the two-dimensional discrete nonnegatively constrained deconvolution problem, whose goal is to reconstruct an object x⁎ from its image b obtained through an optical system and affected by noise. When the large size of the problem prevents regularization through a direct method, iterative...

Full description

Saved in:
Bibliographic Details
Published in:Applied numerical mathematics 2014-01, Vol.75, p.154-166
Main Authors: Favati, P., Lotti, G., Menchi, O., Romani, F.
Format: Article
Language:English
Subjects:
Constraints
Deconvolution
Experimentation
Iterative methods
Mathematical models
Nonnegatively constrained deconvolution
Regularization
Stopping rules
Strategy
Two dimensional
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:We consider the two-dimensional discrete nonnegatively constrained deconvolution problem, whose goal is to reconstruct an object x⁎ from its image b obtained through an optical system and affected by noise. When the large size of the problem prevents regularization through a direct method, iterative methods enjoying the semi-convergence property, coupled with suitable strategies for enforcing nonnegativity, are suggested. For these methods an accurate detection of the stopping index is essential. In this paper we analyze various stopping rules and, with the aid of a large experimentation, we test their effect on three different widely used iterative regularizing methods.
ISSN:0168-9274
1873-5460
DOI:10.1016/j.apnum.2013.07.006