An Adaptive Non Local Spatial Fuzzy Image Segmentation Algorithm

摘要

Fuzzy c-means clustering algorithm (FCM) is one of the most widely used methods for image segmentation. In order to overcome the sensitivity of FCM to noise in images, we introduce a novel non local adaptive spatial constraint term, which is defined by using the non local spatial information of pixels, into the objective function of FCM and propose an adaptive non local spatial fuzzy image segmentation algorithm (ANLS_FIS). In this method, the non-local spatial information of each pixel plays a different role in image segmentation. ANLS_FIS can effectively deal with noise while preserving the geometrical edges in the image. Experiments on synthetic and real images, especially magnetic resonance (MR) images, show that ANLS_FIS is more robust than the modified FCM algorithms with local spatial constraint.