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TIAN Xiao-lin;JIAO Li-cheng;GOU Shui-ping
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Abstract: Because the spatial information is not considered in the traditional fuzzy c-means (FCM) clustering algorithm, the serious inaccuracies with synthetic aperture radar (SAR) image segmentation can be caused by using the FCM algorithm. To improve the SAR image segmentation result, the weighted spatial membership and weighted spatial function are introduced into the FCM algorithm in this paper. The weighted spatial membership is composed of the weighted membership of the relative location and intensity of neighboring pixels under the condition of the multi-scale space. The influence degrees of the weighted spatial membership on the weighted spatial function are optimized by the adaptive genetic algorithm (AGA). The final membership of each pixel is adjusted by the weighted spatial function. Due to the introduction of the optimized spatial information during the process of clustering, the influence of the speckle in SAR images is minimized and the classification accuracy is improved. In our experiments, the real SAR images are segmented and the segmentation results demonstrate the superiority of the proposed algorithm to other methods. This algorithm is not sensitive to the initial segmentation result and is robust to despeckling.
Key words: synthetic aperture radar (SAR) image segmentation, fuzzy c-means (FCM) clustering algorithm, weighted spatial function, adaptive genetic algorithms (AGA)
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TIAN Xiao-lin;JIAO Li-cheng;GOU Shui-ping. SAR image segmentation using optimized FCM with weighted spatial function [J].J4, 2008, 35(5): 846-852.
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URL: https://journal.xidian.edu.cn/xdxb/EN/
https://journal.xidian.edu.cn/xdxb/EN/Y2008/V35/I5/846
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