Synthetic Aperture Radar Image Segmentation Using Modified Fuzzy C-Means and Wavelet Texture Profiles

International Journal of Computer Science and Technology | Vol. 8, No. 3, March 2006 | pp. 17–24

DOI: 10.46882/2006/IJCST/080318

Research Article

Title: Synthetic Aperture Radar Image Segmentation Using Modified Fuzzy C-Means and Wavelet Texture Profiles

Names of Authors: Igor Ivanov¹, Chao-Chun Lin²

Authors’ Affiliations: ¹Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University, Moscow, Russia; ²Department of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan

Abstract:
Speckle noise presents a persistent challenge in extracting distinct land-cover regions from Synthetic Aperture Radar (SAR) imagery. This study implements an un-supervised image segmentation architecture that incorporates multi-scale wavelet texture features into a modified Fuzzy C-Means (FCM) clustering algorithm. The algorithm extracts spatial context descriptors from spatial gray-level dependence matrices in the wavelet domain, while a local spatial penalty function balances gray-level variations during clustering. The algorithm was validated on radar imagery from the ERS-2 satellite. Experimental results demonstrate a segmentation classification accuracy of 94.12%, outperforming standard FCM techniques by 11.4%. The modified penalty framework reduced speckle noise distortion indexes by a factor of 2.6 without losing structural boundary details. The algorithm completed full image matrix cluster profiling within an average window of t = 1.84 seconds, establishing a reliable process for automated satellite mapping systems.

Keywords: Synthetic Aperture Radar, Image Segmentation, Fuzzy C-Means, Wavelet Transform, Texture Analysis

Manuscript Timeline: Received December 02, 2005; Revised January 15, 2006; Accepted February 08, 2006; Published March 24, 2006

Citation: Ivanov, I., & Lin, C. C. (2006). Synthetic Aperture Radar Image Segmentation Using Modified Fuzzy C-Means and Wavelet Texture Profiles. International Journal of Computer Science and Technology, 8(3), 17–24.

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