Parallel iterative median-type algorithms for image processing
151. Hong Tang, B. B. Zhou,
I. D. G. Macleod and R. P. Brent,
A class of parallel iterative median-type algorithms
for efficient image processing,
Proceedings of the International Conference on
Systems, Control and Information - Methodologies and Applications
(ICSCI), Wuhan, China, 1994, 21-28.
Abstract
This paper proposes a class of parallel iterative median-type filters to
restore signals degraded by Gaussian noise. An efficient implementation
of these filters on distributed memory MIMD machines is outlined.
Iterative median-type algorithms have been implemented with high efficiency
(greater than 90%) on the Fujitsu AP1000.
We conclude that algorithms of this type are very suitable for
parallel implementation on distributed memory machines.
Comments
For related papers, see
[149,
152].
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