Image segmentation using Directionlet-domain hidden Markov tree models

In this paper, we modeled the Directionlet coefficients of an image using hidden Markov tree (HMT) model and obtained the image segmentation results using model parameter training, multi-scale likelihood computation and the background of neighborhood-based maximum posterior probability. We demonstrate the performance of the proposed method with synthetic mosaic images and SAR images. The experiment results showed that our method obtained more exact boundary and uniform regions.