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A Wavelet-Multifractal Analysis for SAR Image Segmentation

A. El Boustani, A. Ould khal, A. Hamid, E. El Bachari, S. Siddiqui, W. Kinsner


In this paper, we propose a multifractal-based approach to the extraction of textural features from SAR images. We first estimate the Hölder exponents from the continuous wavelet transform of the image, and then we compute the singularity spectrum using affine iterated functions system (IFS). Each fractal component consisting of pixels having the same Hölder exponent can be an attractor of an IFS. Finally, to highlight the edges, we use the K-means algorithm. The spectrum at each point is used as input for the K-means classifier. The theory and the algorithms for this segmentation approach are presented. Experimental results show that the approach is beneficial for SAR image segmentation, demonstrating better segmentation than those obtained by other techniques.


raw SAR data; multifractals; segmentation; iterated function systems.

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