%0 Journal Article
%T Combined unsupervised image segmentation using watershed and hierarchical clustering with MRF<br>分水岭算法和基于MRF的层次聚类相结合的混合无监督图像分割算法
%A ZHANG Kun
%A WANG Shi-tong
%A <br>张鲲
%A 王士同
%J 计算机应用
%D 2007
%I 
%X A new combined multistage method for image segmentation was proposed. In the first stage, an over-segmented image was got using immersion watershed segmentation, and then primitive segmented results were provided for following merging. In the second stage, region based hierarchical clustering was used with a new heuristic computational model to merge adjacent primitive regions spatially. The model was derived from Bayesian method and Markov random field, and contained two interactive components. From experiments with three different kinds of images, the proposed method shows itself as a very effective way in unsupervised image segmentation. The hierarchy model merges regions in a way same as human perception and finishes within several seconds even for complex aerial image.
%K watershed
%K multistage unsupervised segmentation
%K Markov Random Field (MRF)
%K hierarchical clustering
%K Bayesian method<br>分水岭算法
%K 多阶段无监督分割
%K MRF
%K 层次聚类
%K Bayesian方法
%K 改进分水岭算法
%K 图像分割算法
%K 层次聚类
%K 类相
%K 结合
%K 混合
%K 无监督分割
%K hierarchical
%K clustering
%K watershed
%K image
%K segmentation
%K 邻接区域
%K 视觉
%K 行分割
%K 使用
%K 种类
%K 相互作用
%K 分析
%K 分割效果
%K 结果
%K 初始分割
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=14E16CBD27430512A1B93075C528EABA&yid=A732AF04DDA03BB3&vid=DB817633AA4F79B9&iid=38B194292C032A66&sid=B28C697BC3A1BA62&eid=5AE7FA263C8A6D65&journal_id=1001-9081&journal_name=计算机应用&referenced_num=1&reference_num=10