Parallel image restoration using surrogate constraint methods
Date
2007Source Title
Journal of Parallel and Distributed Computing
Print ISSN
0743-7315
Electronic ISSN
1096-0848
Publisher
Academic Press
Volume
67
Issue
2
Pages
186 - 204
Language
English
Type
ArticleItem Usage Stats
217
views
views
318
downloads
downloads
Abstract
When formulated as a system of linear inequalities, the image restoration problem yields huge, unstructured, sparse matrices even for images of small size. To solve the image restoration problem, we use the surrogate constraint methods that can work efficiently for large problems. Among variants of the surrogate constraint method, we consider a basic method performing a single block projection in each step and a coarse-grain parallel version making simultaneous block projections. Using several state-of-the-art partitioning strategies and adopting different communication models, we develop competing parallel implementations of the two methods. The implementations are evaluated based on the per iteration performance and on the overall performance. The experimental results on a PC cluster reveal that the proposed parallelization schemes are quite beneficial.
Keywords
Image restorationLinear feasibility problem
Parallel computing
Surrogate constraint method