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PARAMETERIZED K-MEANS CLUSTERING FOR RAPID HARDWARE DEVELOPMENT TO ACCELERATE ANALYSIS OF SATELLITE DATA [electronic resource].

Published
Washington, D.C. : United States. Dept. of Energy, 2001.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy.
Physical Description
3 pages : digital, PDF file
Additional Creators
Los Alamos National Laboratory, United States. Department of Energy, and United States. Department of Energy. Office of Scientific and Technical Information
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Summary
Reconfigurable hardware has successfully been used to obtain speed-up in the implementation of image processing algorithms over purely software based implementations. At HPEC 2000 111, we described research we have done in applying reconfigurable hardware to satellite image data for remote sensing applications. We presented an FPGA implementation of K-means clustering that exhibited two orders of magnitude speedup over a software implementation.
Report Numbers
E 1.99:la-ur-01-3028
la-ur-01-3028
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Note
Published through SciTech Connect.
01/01/2001.
"la-ur-01-3028"
Submitted to: Fifth Annual Workshop on High Performance Embedded Computing (HPEC 2001), MIT Lincoln Laboratory, September 25-27, 2001.
Gokhale, M.; Theiler, J. P.; Leeser, M.; Belanov, P.; Estlick, M.; Szymanski, J. J.
View MARC record | catkey: 14654649