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

Conference · Mon Jan 01 00:00:00 EST 2001

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 (LANL), Los Alamos, NM (United States)
• Sponsoring Organization: USDOE
• OSTI ID: 975497
• Report Number(s): LA-UR-01-3028; TRN: US201018%%686
• Resource Relation: Conference: Submitted to: Fifth Annual Workshop on High Performance Embedded Computing (HPEC 2001), MIT Lincoln Laboratory, September 25-27, 2001.
• Country of Publication: United States
• Language: English

Related Subjects

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