Fuzzy c-means clustering (FCM) with spatial constraints (FCM_S) is an

effective algorithm suitable for image segmentation. Its effectiveness contributes not

only to introduction of fuzziness for belongingness of each pixel but also to

exploitation of spatial contextual information. Although the contextual information

can raise its insensitivity to noise to some extent, FCM_S (1) still lacks enough

robustness to noise and outliers and (2) is not suitable for revealing non-Euclidean

structure of the input data due to the use of Euclidean distance (L2 norm).