An SMP Soft Classification Algorithm for Remote Sensing

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dc.contributor.authorPhillips, Rhonda D.en
dc.contributor.authorWatson, Layne T.en
dc.contributor.authorEasterling, David R.en
dc.contributor.authorWynne, Randolph H.en
dc.contributor.departmentComputer Scienceen
dc.date.accessioned2013-06-19T14:36:37Zen
dc.date.available2013-06-19T14:36:37Zen
dc.date.issued2012en
dc.description.abstractThis work introduces a symmetric multiprocessing (SMP) version of the continuous iterative guided spectral class rejection (CIGSCR) algorithm, a semiautomated classification algorithm for remote sensing (multispectral) images. The algorithm uses soft data clusters to produce a soft classification containing inherently more information than a comparable hard classification at an increased computational cost. Previous work suggests that similar algorithms achieve good parallel scalability, motivating the parallel algorithm development work here. Experimental results of applying parallel CIGSCR to an image with approximately 10^8 pixels and six bands demonstrate superlinear speedup. A soft two class classification is generated in just over four minutes using 32 processors.en
dc.format.mimetypeapplication/pdfen
dc.identifierhttp://eprints.cs.vt.edu/archive/00001217/en
dc.identifier.sourceurlhttp://eprints.cs.vt.edu/archive/00001217/01/pcigscrCG12.pdfen
dc.identifier.trnumberTR-12-22en
dc.identifier.urihttp://hdl.handle.net/10919/19449en
dc.language.isoenen
dc.publisherDepartment of Computer Science, Virginia Polytechnic Institute & State Universityen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectNumerical analysisen
dc.subjectParallel computationen
dc.subjectAlgorithmsen
dc.subjectData structuresen
dc.titleAn SMP Soft Classification Algorithm for Remote Sensingen
dc.typeTechnical reporten
dc.type.dcmitypeTexten

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