多主体框架下基于FCM的彩色遥感图像分割

为解决大尺度高分辨率遥感图像的数据量大及局部非均匀问题，提出一种在多主体系统（MAS）框架下基于模糊C均值（FCM）的彩色遥感图像分割方法。首先利用规则划分技术将图像域划分为若干个子块，每个分割主体控制一个子块；然后在MAS框架下，分割主体通过FCM算法实现对应子块的初始分割，将初始结果与全局模型协作，确定其区域正确类别数和标号统一；最后通过协调主体协调各分割主体及其邻域分割主体的聚类中心，从而消除遥感图像的局部非均匀性，以实现彩色遥感图像分割。利用提出算法和FCM算法分别对真实彩色遥感图像和合成图像进行了分割试验，并对其分割结果进行定性、定量评价，其结果说明了提出方法的可行性和有效性。

Color Remote Sensing Imagery Segmentation Based FCM within a MAS Framework

For the large-scale remote sensing imagery which has large data and local feature heterogeneity, this paper presents a color remote sensing imagery segmentation method based FCM within a multi-agent system framework.Firstly, dividing the image domain into several sub-domains with rule division tecnology and each segmentation agent controls one sub-domain.And then, the segmentation agent executes the segmentation of its sub-domain by FCM to get the initial local segmentation result within MAS framework, via the harmonizing the local result with the global segmentation result to obtain the true local class number and unify the local label.Finally, the coordinate agent is employed to eliminate the local feature heterogeneity of remote sensing imagery via coordinating the cluster centers of each segmentation agent with its neighbors.The experiments are carried out on the synthetic imagery and the color remote sensing images.The results are qualitatively and quantitatively evaluated and certify the efficiency and effectiveness of the proposed algorithm.