Superiorization of incremental optimization algorithms for statistical tomographic image reconstruction
Loading...
External sources
External sources
Date
Advisor
Coadvisor
Graduate program
Undergraduate course
Journal Title
Journal ISSN
Volume Title
Publisher
Iop Publishing Ltd
Type
Article
Access right
Acesso aberto
External sources
External sources
Abstract
We propose the superiorization of incremental algorithms for tomographic image reconstruction. The resulting methods follow a better path in its way to finding the optimal solution for the maximum likelihood problem in the sense that they are closer to the Pareto optimal curve than the non-superiorized techniques. A new scaled gradient iteration is proposed and three super-iorization schemes are evaluated. Theoretical analysis of the methods as well as computational experiments with both synthetic and real data are provided.
Description
Keywords
superiorization, convex optimization, tomographic image reconstruction
Language
English
Citation
Inverse Problems. Bristol: Iop Publishing Ltd, v. 33, n. 4, 26 p., 2017.
