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.