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Fuzzy c-means (FCM) clustering technique has been widely applied in image segmentation. However, it is quite sensitive to the various noises or outliers. In order to further improve the segmentation accuracy and robustness to noise, a fuzzy nonlinear weighted local information c-means clustering method is proposed for unsupervised segmentation of noisy images in this paper. First, a fuzzy nonlinear weighted factor including both the spatial distance of local window and its gray-level differencedblp:journals/jihmsp/SongCL17 fatcat:3ol3zp2xtrci5ebw26uznup25u