Due to the fuzzy property of image segmentation， this paper proposes a segmentation model for non-uniform gray and high-noise images. The model is based on the fuzzy energy functional which combines with the regional and edge information， and uses the coefficient of variation as the local regional statistics， thus avoiding the interference of noise on the segmentation and extracting the image information well. Regional energy balances the importance of the target and the background， and drives the initial contour toward the target boundary. The edge energy regularizes the pseudo-level set function to maintain the smoothness of the curve evolution. To find the minimum value of the energy functional， the difference between the old and new energy functional is calculated directly so as to update the pseudo level set. The segmentation results of synthetic and real images with high noise， mixed noise and uneven intensity show that the model has a good segmentation effect.