Based on the statistics characteristics of contourlet coefficients,a new multi-scale image segmentation method(CHMTseg)combining Contourlet domain hidden Markov trees model with multiscale Bayesian approaches was presented.A novel weighted neighborhood model was given for preserving more inner-scale information in Contourlet domain.The pixel level segmentation based on Gauss mixture model and the multiscale fusion method based on the new contextual model were provided.In experiments,synthetic mosaic image,aerial image and SAR image were selected to evaluate the performance of the method,and the segmentation results were compared with wavelet domain HMTseg method.For synthetic mosaic texture image,miss classed probability was given as the evaluation of segmentation results.Experiment results show that the method not only has better performance in edges and anisotropy information detection but has lower missed classed probability,and it can achieve satisfied segmentation results for real images.