Fuzzy C-means image classification algorithm based on SSCL
基于SSCL的模糊C均值图像分类方法

An adaptive fuzzy C-means image classification algorithm based on SSCL is proposed, in order to overcome the shortcomings that traditional fuzzy C-means clustering algorithm is noise-sensitive and relies excessively on initial cluster centers. First we obtain the cluster centers using SSCL, then treat the cluster centers as the initial value of fuzzy C-means, so an adaptive image classification can be achieved. At last, post processing is implemented using space information. Experiment results show that proposed algorithm is less sensitive to noise and initial cluster centers in FCM method, and has better classification accuracy.