Speaker
Dr
Mihnea Dulea
(National Institute of Physics and Nuclear Engineering)
Description
Hyperspectral image processing still requires nowadays considerable computational and storage resources, beyond the available ones for a single server. In particular, clustering of images gathered from the current satellites can be done in a reasonable time only using high performance computing facilities.
In this paper we discuss the latest approaches for fuzzy clustering techniques that are adapted to work on hundreds of processors as well as the pre-processing techniques for data splitting and reading. Comparisons between different techniques are based on implementations for BlueGene/P.
The paper exposes part of the concepts presented in [1] and [2],
as well as experimental results.
[1] D. Petcu, D. Zaharie, S. Panica, A. S. Hussein, A. Sayed, H. El-Shishiny, “Fuzzy Clustering of Large Satellite Images using High Performance Computing,” In Proceedings of SPIE Volume 8183, SPIE Remote Sensing Conference: High-Performance Computing in Remote Sensing, http://dx.doi.org/10.1117/12.898281, 2011
[2] A.C. Toma, S. Panica, D. Zaharie, D. Petcu, "Computational Challenges in Processing Large Hyperspectral Images", submitted to Grid, Cloud & High Performance Computing Science", RO-LCG 2012, October 2012
Primary author
Mr
Silviu Panica
(West University of Timisoara)
Co-authors
Prof.
Dana Petcu
(West University of Timisoara)
Prof.
Daniela Zaharie
(West University of Timisoara)
