模糊局部均值聚类分割法改进及其应用

被引:4
作者
刘璐
吴成茂
机构
[1] 西安邮电大学电子工程学院
基金
国家自然科学基金重点项目;
关键词
聚类分析; 图像分割; 模糊C-均值聚类; 模糊局部C-均值聚类; 分割结果;
D O I
10.16208/j.issn1000-7024.2015.12.039
中图分类号
TP391.41 [];
学科分类号
080203 ;
摘要
为改善传统模糊C-均值聚类算法的抗噪性能,Krinidis和公茂果等提出像素局部邻域信息模糊C-均值聚类算法系列,但其存在聚类中心表达式与聚类目标函数不一致的问题。利用拉格朗日乘子将模糊局部信息聚类目标函数和隶属度约束条件相结合,构造无约束优化函数,利用函数极值存在的必要条件推导该聚类新的隶属度和聚类中心迭代表达式,设计一种核空间模糊局部信息C-均值聚类分割算法。人工合成图像和实际遥感图像分割测试结果表明,该算法明显优于现有模糊局部信息C-均值聚类分割法,针对复杂遥感图像能获得更好的分割效果。
引用
收藏
页码:3365 / 3369+3407 +3407
页数:6
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