Based on the Enhanced EM Model Overlap Region Image Segmentation Algorithm

In image large-scale overlap region of the effective segmentation is always a difficult problem,the traditional Log operator,Sobel operator,Canny operator and gradient operator and algorithms to solve large scale pixel overlap problem,model will in no convergence situation,causing segmentation effect is bad,in order to solve this problem,the paper proposes a kind of enhanced EM model is used to solve the problem of overlapping area image segmentation,use curvelet transform in curvelet domain of images edge features,and positioning characteristic curvelet coefficient.Through the enhancement features curvelet coefficient,enhance the edge feature of kriging,multi-scale segmentation more structural elements morphological detection edge image,and eliminate the interference of overlapping brings.The simulation results show that the edge of the segmentation is more complete and accurate,and satisfactory results have been obtained.