Hybrid Multiphase Segmentation Model And Algorithm For Integration Statistical Image Information

As a basic digital image processing technology,image segmentation is widely used in various fields of production and life.For the problems existing in the traditional active contour model,such as initial contour selection,noise pollution,complex texture boundaries and image gray unevenness,the paper makes full use of various statistical information to combination mixed activity models and multi-phase levels.This paper proposes the improved Laplace adaptive multiphase segmentation model and the robust multiphase segmentation model based on local and global fitting.In the improved Laplace adaptive multiphase segmentation model,gradient pre-weighted smoothing and median filtering are combined to preprocess the image,and the structural tensor is introduced to automatically define the initial contour.In the global term,the improved zero-crossing Laplacian fitting energy is added to improve the positioning ability of the weak boundary.An adaptive segmentation fitting term is added to the global term to improve the segmentation effect of intensity inhomogeneous.In the local fitting term,the Gaussian kernel function with local gray mean and variance is used for segmentation.A weighting coeffcient equation is introduced to balance the weights of local and global terms.Experiments show that the LGLAF model has strong anti-noise ability and has a good effect on inhomogeneous images.In the robust multiphase segmentation model based on local and global fitting,a combination of multi-scale information enhancement and anisotropic tensor diffusion filtering is proposed to de-noise and preserve texture details,and the initial contour is obtained by combining two-dimensional maximum entropy and improved genetic algorithm.In the global term,the Laplace fitting energy function is reconstructed by using various local feature variables.A segmentation model with controlled depth and depth coefficient is proposed to better segment the complex topology.In the local term,the LGDF model is used to process the gray uneven region.The model uses the exponential function as the speed stopped function,and adds the robust curve evolution stopping condition to improve the segmentation efficiency.Experiments show that the HMDLG model has a better segmentation effect on gray-scale inhomogeneous images with complex internal structures and texture features.