%0 Journal Article
%T Change detection for SAR images based on quantum-inspired immune clonal clustering algorithm<br>基于量子免疫克隆聚类的SAR图像变化检测
%A LI Yang-Yang
%A WU Na-N
%A JIAO Li-Cheng
%A SHANG Rong-Hua
%A LIU Ruo-Chen
%A <br>李阳阳
%A 吴娜娜
%A 焦李成
%A 尚荣华
%A 刘若辰
%J 红外与毫米波学报
%D 2011
%I Science Press
%X As the conventional evolutionary clustering optimization methods are often time-consuming and easy to trap in local optimal value in dealing with the problem of change detection. Furthermore, it can not detect the edge accurately for SAR images. We propose the change detection for SAR images based on the clustering analysis. The proposed method takes gray-levels as an input, uses the quantum bit to define the clustering center, and searches the optimal cluster center using the quantum-inspired immune clonal algorithm and gets the global threshold. Finally, the change-detection map is produced. Compared with K&I threshold, it can achieve the better value, and compared with Genetic Algorithm Based Clustering (GAC), the proposed method can search the more better clustering center quickly and effectively, besides, it can detect the accurate edge, improve the change detection accuracy.
%K Change Detection
%K SAR Images
%K Clustering
%K Quantum-Inspired Immune Clona Algorithm<br>变化检测
%K SAR图像
%K 聚类
%K 量子免疫克隆算法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=1319827C0C74AAE8D654BEA21B7F54D3&jid=D3B4F771D1A06062008B4D0A2EF05996&aid=F1433D9E74E9C1DF98B7E916D25077D4&yid=9377ED8094509821&vid=340AC2BF8E7AB4FD&iid=E158A972A605785F&sid=965F4E89CD0AFC30&eid=09D368C679EC819B&journal_id=1001-9014&journal_name=红外与毫米波学报&referenced_num=0&reference_num=0