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Parallel Implementation of Hyperspectral Image Processing Algorithms
2006
2006 IEEE International Symposium on Geoscience and Remote Sensing
High computing performance of algorithm analysis is essential in many hyperspectral imaging applications, including automatic target recognition for homeland defense and security, risk/hazard prevention and monitoring, wild-land fire tracking and biological threat detection. Despite the growing interest in hyperspectral imaging research, only a few efforts devoted to designing and implementing well-conformed parallel processing solutions currently exist in the open literature. With the recent
doi:10.1109/igarss.2006.242
dblp:conf/igarss/PlazaVPSMB06
fatcat:3hyv7i362jdf3fdc4dqa4slrxe