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Remote Sensing Classification Using Fuzzy C-means Clustering with Spatial Constraints Based on Markov Random Field
European Journal of Remote Sensing
This paper proposes a new clustering algorithm which integrates Fuzzy C-means clustering with Markov random field (FCM). The density function of the first principal component which sufficiently reflects the class differences and is applied in determining of initial labels for FCM algorithm. Thus, the sensitivity to the random initial values can be avoided. Meanwhile, this algorithm takes into account the spatial correlation information of pixels. The experiments on the synthetic and QuickBirddoi:10.5721/eujrs20134617 fatcat:4noyqe4bk5cfzov3ensixcxyki