基于并行Tabu搜索和空间信息约束的遥感影像模糊聚类
Fuzzy C-Means Clustering of Remote Sensing Imagery Using Parallel Tabu Search and Spatial Relation Constrained
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摘要: 在传统模糊C-均值聚类的基础上,引入了描述空间邻近关系的空间隶属度;采用Tabu搜索策略,抑制了模糊聚类的局部收敛性和对聚类中心初值的敏感性;提出了并行算法,有效地降低了影像分割的通信复杂度,提高了算法的搜索速度,实现了线性加速比。实验结果表明,改进算法有效地提高了聚类抗噪性能,减少了聚类迭代次数。Abstract: Based on the classical FCM clustering,the spatial fuzzy membership about a pixel and regions is defined and constrained into the classical partition matrix.Tabu search was introduced to overcome the locality and the sensitiveness of the initial condition of FCM clustering.A FCM algorithm based on Tabu search is parallelized to reduce the communication complexity of image segmentation and to improve the overall performance of the scheme,which achieves a satisfied linear speedup.The experimental results show the efficiency of the proposed algorithm in decreasing clustering iterations and increasing classified precision.
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