Parallel Evolution of Image Processing Tools for Multispectral Imagery

摘要

We describe the implementation and performance of a parallel, hybrid evolutionary-algorithm based system, which optimizes image processing tools for feature finding tasks in multi-spectral imagery (MSI)data sets. Our system uses an integrated spatial-spectral approach and is capable of combining suitably-registered data from different sensors. We investigate the speed-up obtained by parallelization of the evolutionary process via multiple processors (a workstation cluster) and develop a model for prediction of run-times for different numbers of processors. We demonstrate our system on Landsat Thematic Mapper MSI , covering the recent Cerro Grande fire at Los Alamos, NM, USA.