JUCS - Journal of Universal Computer Science 3(7): 821-834, doi: 10.3217/jucs-003-07-0821
Stack Filter Design Using a Distributed Parallel Implementation of Genetic Algorithms
expand article infoPeter E. Undrill‡, Kostas Delibasis‡, George G. Cameron‡
‡ University of Aberdeen, United Kingdom

Corresponding author: Peter Undrill ( undrill@biomed.abdn.ac.uk )

© Peter Undrill, Kostas Delibasis, George Cameron.
This article is freely available under the J.UCS Open Content License.
Citation: Undrill PE, Delibasis K, Cameron GG (1997) Stack Filter Design Using a Distributed Parallel Implementation of Genetic Algorithms. JUCS - Journal of Universal Computer Science 3(7): 821-834. https://doi.org/10.3217/jucs-003-07-0821
Open Access
Abstract
Stack filters are a class of non-linear spatial operators used for suppression of noise in signals. In this work their design is formulated as an optimisation problem and a method that uses Genetic Algorithms (GAs) to perform the configuration is explained. Because of its computational complexity the process has been implemented as a distributed parallel GA using the Parallel Virtual Machine (PVM) software. We present the results of applying our stack filters to the restoration of magnetic resonance (MR) images corrupted with uniform, uncorellated, noise showing improved statistical performance compared with the median filter and indicating better retention of image details. The efficiency of the parallel implementation is examined, addressing both algorithmic and data decomposition, showing that execution times can be significantly reduced by distributing the task across a network of heterogeneous processors.
Keywords
Distributed Computation, Genetic Algorithms, Stack Filters, Image Processing