Abstract
We describe the implementation and performance of a
parallel, hybrid evolutionary-algorithm based system,
which optimises image processing tools for
feature-finding tasks in multi-spectral imagery (MSI)
data sets. Our system uses an integrated
spatio-spectral approach and is capable of combining
suitably-registered data from different sensors. We
investigate the speed-up obtained by parallelisation of
the evolutionary process via multiple processors (a
workstation cluster) and develop a model...
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