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International Parallel and Distributed Processing Symposium (IPDPS'03)
Distributed Geo-Rectification of Satellite Images Using Grid Computing
Nice, France
April 22-April 26
ISBN: 0-7695-1926-1
ASCII Text
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Y. M. Teo, S. C. Low, S. C. Tay, J. P. Gozali, "Distributed Geo-Rectification of Satellite Images Using Grid Computing," Parallel and Distributed Processing Symposium, International, pp. 15b, International Parallel and Distributed Processing Symposium (IPDPS'03), 2003.
 
 
BibTex
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@article{ 10.1109/IPDPS.2003.1213093,
author = {Y. M. Teo and S. C. Low and S. C. Tay and J. P. Gozali},
title = {Distributed Geo-Rectification of Satellite Images Using Grid Computing},
journal ={Parallel and Distributed Processing Symposium, International},
volume = {0},
year = {2003},
issn = {1530-2075},
pages = {15b},
doi = {http://doi.ieeecomputersociety.org/10.1109/IPDPS.2003.1213093},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Parallel and Distributed Processing Symposium, International
TI - Distributed Geo-Rectification of Satellite Images Using Grid Computing
SN - 1530-2075
SP
EP
A1 - Y. M. Teo,
A1 - S. C. Low,
A1 - S. C. Tay,
A1 - J. P. Gozali,
PY - 2003
KW - null
VL - 0
JA - Parallel and Distributed Processing Symposium, International
ER -
 
Y. M. Teo, National University of Singapore
S. C. Low, National University of Singapore
S. C. Tay, National University of Singapore
J. P. Gozali, National University of Singapore
Grid computing seeks to aggregate computing resources within an enterprise and leverage on resources you don?t own for compute-intensive applications. Geo-rectification is a process for correcting spatial location and orientation of a satellite image. This paper focuses on the parallelization of the compute-intensive satellite image geo-rectification problem on a cluster grid. We discuss our approach to data and task partitioning, visualization technique and the archival of data. The computational tasks include wrapping satellite positional data to compensate the earth curvature, and consist of several steps such as image re-sampling, resolution conversion and image matching. Experimental results obtained using commodity PCs are discussed.
Citation:
Y. M. Teo, S. C. Low, S. C. Tay, J. P. Gozali, "Distributed Geo-Rectification of Satellite Images Using Grid Computing," ipdps, pp.15b, International Parallel and Distributed Processing Symposium (IPDPS'03), 2003
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