UPM Institutional Repository

Limited memory methods with improved symmetric rank-one updates and its applications on nonlinear image restoration


Citation

Khiyabani, Farzin Modarres and Leong, Wah June (2014) Limited memory methods with improved symmetric rank-one updates and its applications on nonlinear image restoration. Arabian Journal for Science and Engineering, 39 (11). pp. 7823-7838. ISSN 1319-8025; ESSN: 1319-8025

Abstract

The iterative solution of unconstrained optimization problems has been found in a variety of significant applications of research areas, such as image restoration. In this paper, we present an efficient limited memory quasi-Newton technique based on symmetric rank-one updating formula to compute meaningful solutions for large-scale problems arising in some image restoration problems. Numerical experiments and comparisons on various well-known methods in the literature are presented to illustrate the effectiveness of the proposed method particularly for images of large size.


Download File

Full text not available from this repository.

Additional Metadata

Item Type: Article
Divisions: Faculty of Science
DOI Number: https://doi.org/10.1007/s13369-014-1357-3
Publisher: Springer Berlin Heidelberg
Keywords: Large-scale optimization; Image restoration; Quasi-Newton methods; Limited memory scheme; Symmetric rank-one update
Depositing User: Nurul Ainie Mokhtar
Date Deposited: 18 Jan 2016 06:14
Last Modified: 18 Jan 2016 06:14
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1007/s13369-014-1357-3
URI: http://psasir.upm.edu.my/id/eprint/34383
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item