基于FCM聚类的形势场图像分割方法研究

Research on Situation Field Image Segmentation Based on FCM Clustering

摘要: 本文研究基于FCM聚类算法的天气形势场图像分割问题，首先通过解析将气象中心历史再分析资料中多种形势场数据可视化绘制出高空天气图像，再结合本文所研究的问题对FCM聚类算法的原理以及步骤进行描述，然后将FCM聚类算法应用于高空天气图像以及形势场数据可视化过程中可能带有噪声的高空天气图像的分割，最后通过实验结果验证FCM聚类算法能够较好地实现形势场可视化图像的分割，进而标注出高空天气图像中等值线。

Abstract: In this paper, the FCM clustering algorithm is used to solve the problem of weather situation field image segmentation. First, the high-altitude weather images are drawn by analyzing and visualizing various situation field data in the historical reanalysis data of the meteorological center. Then, the principle and steps of FCM clustering algorithm are described based on the problems studied in this paper. Then the FCM clustering algorithm is applied to the segmentation of the high-altitude weather images and the high-altitude weather images that may contain noise in the process of situation field data visualization. The experimental results show that the FCM clustering algorithm can achieve better segmentation of the situation field visualization images, and then the is olines in the high-altitude weather images can be marked.