PARAMETERIZED K-MEANS CLUSTERING FOR RAPID HARDWARE DEVELOPMENT TO ACCELERATE ANALYSIS OF SATELLITE DATA

Conference · Sun Dec 31 23:00:00 EST 2000

OSTI ID:975497

Belanov, P ^[1]; Estlick, M ^[2]; Gokhale, M ^[3]; Szymanski, J J ^[4]; Theiler, J P ^[5]

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1. Pavle
2. Michael
3. Maya
4. John J.
5. James P.

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.

• Research Organization: Los Alamos National Laboratory
• Sponsoring Organization: DOE
• OSTI ID: 975497
• Report Number(s): LA-UR-01-3028
• Country of Publication: United States
• Language: English

Related Subjects

97 MATHEMATICS AND COMPUTING
ALGORITHMS
DATA ANALYSIS
IMAGE PROCESSING
IMPLEMENTATION
PERFORMANCE
REMOTE SENSING
SATELLITES