%0 Journal Article
%T General Hybridized PSO with Chaos for Fast Infrared Image Segmentation Method<br>基于广义混沌混合PSO的快速红外图像分割算法
%A NI Chao
%A LI Qi
%A XIA Liang-Zheng
%A <br>倪超
%A 李奇
%A 夏良正
%J 光子学报
%D 2007
%I 
%X To detect infrared objects accurately, a fast infrared image segmentation method based on general hybridized PSO with chaos is proposed. The method of 2-D maximum fuzzy partition entropy can obtain better segmentation,because it takes advantage of gray and spatial neighboring information, and fuzziness of image also is taken into consideration. In essence,it is a typical nonlinear integer programming problem with huge searching space and many local optima. General hybridized PSO with chaos is based on general PSO, and it makes use of adaptive balance searching strategy. When the evolution stops, simulated annealing algorithm is introduced to select the current global optimum to be chaotic optimized for the sake of enhancing local searching ability and overcoming premature convergence. Experimental results show that the method can segment infrared image quickly and stably.
%K Infrared image segmentation
%K 2-D maximum fuzzy partition entropy
%K GPSO
%K Chaotic optimization<br>红外图像分割
%K 二维模糊划分最大熵
%K 广义PSO
%K 混沌优化
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=6E709DC38FA1D09A4B578DD0906875B5B44D4D294832BB8E&cid=47EA7CFDDEBB28E0&jid=9F6139E34DAA109F9C104697BF49FC39&aid=E7658AFBBC737817391C4143B4B536E3&yid=A732AF04DDA03BB3&vid=933658645952ED9F&iid=F3090AE9B60B7ED1&sid=D68286E0C08ACACF&eid=AC45B356D9DF3BDB&journal_id=1004-4213&journal_name=光子学报&referenced_num=0&reference_num=12