Parameter Estimation and Two Step Segmentation Based on Mumford-Shah Model
Zhengwen Li, Weiwei Wang, Peng‐Lang Shui · Dianzi xuebao · 2006
Mumford and Shah's variational model in the 2-phase piecewise constant case is very efficient in image segmentation.However,if the original image is contaminated by some noise,the level set method for solving the model is very sensitive to the initial level set function and the parameter of the length of the evolving contour.Here we propose a two-step segmentation method,where in the first step,a coarse segmentation is obtained by using some traditional method,and in the second step,the coarse segmentation is used as an initial solution in the variational model.Moreover,we gave a model for adaptively estimating the parameter of the length of the evolving contour,where the parameter is defined as an increasing function of the variance of the noise.Combination of the two-step segmentation and the adaptive estimation model not only enables automatic evolution but also ensures fast and accurate partition.Experiment on some computer-produced images and real images shows that the algorithm proposed here is very efficient.