Abstract
A novel unsupervised classification scheme called spatial fuzzy C-means clustering is proposed in this article. Based on conventional fuzzy C-means algorithm, our scheme takes spatial homogeneity into consideration by introducing spatial membership and applying SMNF, thus improved robustness against noises or outliers. Preliminary experimental results are also shown to demonstrate effectiveness of our method.
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