Considering the dependencies between the coefficients and their parents

a non Gaussian bivariate distribution model is given in non subsampled Contourlet transform domain. A novel non subsampled Contourlet transform segmentation method based on the bivariate model is proposed. In experiments

synthetic mosaic image and real images were selected to evaluate the performance of the method

and the segmentation results were compared with wavelet domain hidden Markov tree model method and contourlet domain hidden markov tree model segmentation method. The simulation results indicate that the proposed method has better performance

such as keeps better visual result and reserves more information in edges. As a simple model

the time complexity for model training is lower than other models in comparison experiments.