%0 Journal Article
%T Image Segmentation Based on Multiscale Markov Random Field<br>基于多尺度马尔可夫随机场的图像分割
%A WANG Xi-Li JIAO Li-Cheng
%A <br>汪西莉
%A 焦李成
%J 计算机科学
%D 2003
%I 
%X 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.
%K Multiscale markov random field(MRF)
%K Noniterative algorithm
%K Iterative algorithm
%K Maximizer of the posterior marginals (MPM)
%K Expectation maximization (EM)<br>图像分割
%K 图像像素
%K 多尺度马尔可夫随机场
%K 图像边缘
%K 图像处理
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=E0883BE0AC6D9EA5&yid=D43C4A19B2EE3C0A&vid=340AC2BF8E7AB4FD&iid=DF92D298D3FF1E6E&sid=0584DB487B4581F4&eid=5BC9492E1D772407&journal_id=1002-137X&journal_name=计算机科学&referenced_num=2&reference_num=6