Image Segmentation Based on Multiscale Markov Random Field
基于多尺度马尔可夫随机场的图像分割

The noniterative algorithm of multiscale MRF has much lower computing complexity and better result than its iterative counterpart of noncausal MRF model, since it has causality property between scales, and such causality is consistent with the character of images. Maximizer of the posterior marginals (MPM)algorithm of multiscale MRF model is presented for only one image can be obtained in image segmentation. EM algorithm for parameter estimate is also given. Experiments demonstrate that comparing with iterative ones, the proposed algorithms have the characteristics of greatly reduced computing time and better segmentation results. This is more notable for large images.