On the Splitting Algorithm Based on Multi-target Model for Image Segmentation

Abstract

Against to the different regions of membership functions indicated image in the traditional image segmentation variational model, resulting segmentation is not clear, de-noising effect is not obvious problems, this paper proposes multi-target model for image segmentation and the splitting algorithm. The model uses a sparse regularization method to maintain the boundaries of segmented regions, to overcome the disadvantages of segmentation fuzzy boundaries resulting from total variation regularization. The algorithm uses the multi-scale geometric analysis tool to maintain the geometry of image, which multi-scale geometric transformations can be flexibly selected according to actual problems. Experimental results show that: the proposed model and the algorithm are feasible and effective.