Anti-noise quick fuzzy-clustering digital image segmentation method

The invention discloses an anti-noise quick fuzzy-clustering digital image segmentation method. The method includes the steps of performing feature extraction of an image to be segmented to obtain a feature data set X of the image; using the feature data set X and neighborhood information of the image to perform anti-noise pretreatment of an original image; initializing a cluster center by a K-means algorithm; calculating a fuzzy membership matrix; updating the fuzzy membership matrix through a space function based on space information construction; calculating the cluster center and a targeted function value used for implementing cluster segmentation based on the updated fuzzy membership matrix; performing loop iteration; and acquiring probability of data points belonging to a certain type according to a fuzzy membership matrix subjected to cluster output, and segmenting the image by performing classification markup to each data point according to the maximum probability principle. Satisfactory image segment