基于模糊C-均值聚类的遥感影像分类
lassification of Remote Sensing Image Based on fuzzy C-Means Clustering
为了很好地解决遥感影像分类的问题,在Matlab平台基础上,采用模糊C-均值聚类算法对遥感影像进行非监督分类,首先介绍了模糊C-均值聚类算法,并根据此算法思想,构造了模糊C-均值分类器,然后对遥感影像进行分类,输出分类后影像,并用混淆矩阵进行了精度评定。精度评定结果表明,实验取得了较好的成果。
In order to solve the problem of the classification of remote sensing image, fuzzy C-Means Clustering are adopted to finish the unsupervised classification of remote sensing image based on Matlab. Fuzzy C-Means Clustering algorithm is introduced first and according to the algorithm above, fuzzy classifier is established to realize the classification of the remote sensing image. Then the classified image is outputted and the precision of classification result is assessed with Confusion-Matrix. The result of accuracy assessment shows that the classification method gets a comparatively good precision.
罗卿莉
遥感技术
模糊C-均值聚类遥感影像分类
fuzzy C-Means Clusteringremote sensing imageclassificationConfusion-Matrix
罗卿莉.基于模糊C-均值聚类的遥感影像分类[EB/OL].(2008-04-07)[2025-08-02].http://www.paper.edu.cn/releasepaper/content/200804-165.点此复制
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