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Proceedings Paper

Robust optimal fuzzy clustering algorithm applicable to multispectral and polarimetric synthetic aperture radar images
Author(s): Salim Chitroub; Amrane Houacine; Boualem Sansal
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Paper Abstract

In clustering algorithms, there are two problems arising. The first one is the cluster validation. The second one is that the clustering algorithms are similar to descent algorithms, which provide only a local optimization. In this paper, a robust optimal fuzzy clustering algorithm applicable to multispectral and polarimetric synthetic aperture radar (SAR) images is suggested. The idea of the proposed optimal fuzzy clustering algorithm is to build an objective function whose global minimum will characterize a good fuzzy partition of the training data set. To reach such a global minimum we use simulated annealing (SA) algorithm. An adaptation of SA to the fuzzy clustering problem is then established. By robust algorithm, we mean that it leads to classification results that are robust versus the estimated number of clusters. To find the number of clusters that leads to a robust classification, we compare between two different classification results and founding correspondence between their clusters without referencing to the ground truth. We consider such a comparison criterion as an optimization problem, which will be solved by using a new optimization technique based on correspondence analysis. The technique is inspired from SA method. We demonstrate our methodology by classifying two different complex scenes using a multispectral data provided by SPOT satellite and the SIR-C data.

Paper Details

Date Published: 14 December 1999
PDF: 12 pages
Proc. SPIE 3871, Image and Signal Processing for Remote Sensing V, (14 December 1999); doi: 10.1117/12.373236
Show Author Affiliations
Salim Chitroub, Univ. of Sciences and Technology Houari Boumedienne (Algeria)
Amrane Houacine, Univ. of Sciences and Technology Houari Boumedienne (Algeria)
Boualem Sansal, Univ. of Sciences and Technology Houari Boumedienne (Algeria)


Published in SPIE Proceedings Vol. 3871:
Image and Signal Processing for Remote Sensing V
Sebastiano Bruno Serpico, Editor(s)

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