Parallel iterative noise filters for real-time image processing
152. Hong Tang, B. B. Zhou,
I. D. G. Macleod, R. P. Brent and Wei Sun,
Comparisons of parallel iterative noise filters for real-time image
processing, Proc. Fifth International Conference on Signal
Processing Applications and Technology (ICSPAT),
Dallas, Texas, 1994, Vol. 2, 1015-1020.
Abstract
In this paper, we investigate two parallel iterative noise filters for
restoration of noise-degraded images. These filters are analysed
and evaluated in terms of their filtering performance under practical noise
conditions, with signal-to-noise ratios ranging from 0dB to 10dB.
The parallel iterative noise filters have been implemented with high efficiency
on a Fujitsu AP1000 mesh-connected array processor. The algorithms
and their method of parallel implementation are presented together with
the results of extensive experiments which demonstrate the effectiveness
and speed of the filters. We conclude that these two forms of parallel
filter are promising candidates for real-time image restoration.
Comments
For related papers, see
[149,
151].
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