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Proceedings Paper

Fuzzy clustering of large satellite images using high performance computing
Author(s): Dana Petcu; Daniela Zaharie; Silviu Panica; Ashraf S. Hussein; Ahmed Sayed; Hisham El-Shishiny
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Paper Abstract

Fuzzy clustering is one of the most frequently used methods for identifying homogeneous regions in remote sensing images. In the case of large images, the computational costs of fuzzy clustering can be prohibitive unless high performance computing is used. Therefore, efficient parallel implementations are highly desirable. This paper presents results on the efficiency of a parallelization strategy for the Fuzzy c-Means (FCM) algorithm. In addition, the parallelization strategy has been extended in the case of two FCM variants, which incorporates spatial information (Spatial FCM and Gaussian Kernel-based FCM with spatial bias correction). The high-level requirements that guided the formulation of the proposed parallel implementations are: (i) find appropriate partitioning of large images in order to ensure a balanced load of processors; (ii) use as much as possible the collective computations; (iii) reduce the cost of communications between processors. The parallel implementations were tested through several test cases including multispectral images and images having a large number of pixels. The experiments were conducted on both a computational cluster and a BlueGene/P supercomputer with up to 1024 processors. Generally, good scalability was obtained both with respect to the number of clusters and the number of spectral bands.

Paper Details

Date Published: 12 October 2011
PDF: 18 pages
Proc. SPIE 8183, High-Performance Computing in Remote Sensing, 818302 (12 October 2011); doi: 10.1117/12.898281
Show Author Affiliations
Dana Petcu, West Univ. of Timisoara (Romania)
Daniela Zaharie, West Univ. of Timisoara (Romania)
Silviu Panica, West Univ. of Timisoara (Romania)
Ashraf S. Hussein, Ain Shams Univ. (Egypt)
Ahmed Sayed, IBM Ctr. for Advanced Studies in Cairo (Egypt)
Hisham El-Shishiny, IBM Ctr. for Advanced Studies in Cairo (Egypt)


Published in SPIE Proceedings Vol. 8183:
High-Performance Computing in Remote Sensing
Bormin Huang; Antonio J. Plaza, Editor(s)

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