Improved Fuzzy C-mean Classifier and Comparison Study of Its Clustering Results of Satellite Remotely Sensed Data

This article presents an improved fuzzy c-mean classifier in which Mahalanobis distance is adopted using standard connivance matrix, shown as ellipse spheroid cluster algorithm. This methodis more likely close to remote sensing data scatter map then that of other cluster algorithm so that the classification results are better either. Satellite ASTER Beijing data is used for testing the results proved that the improved the Mahalanobis distance classifier is more precedence than k-mean classifier and fuzzy c-mean classifier.