基于有监督模糊C-均值算法的混合像元分解

Decomposition of Mixed Pixels Based on Supervisory FCM

遥感影像中普遍存在混合像元,混合像元的分解是遥感图像处理的一大难点,同时也是人们研究的热点。使用有监督的模糊C-均值算法对遥感影像的混合像元进行分解。在传统的模糊C-均值算法的基础上结合先验知识引入优化初始聚类中心的方法,结合通过降采样产生的模拟数据、ETM遥感影像和MODIS遥感影像对算法性能进行了实验。结果表明,算法适用于多光谱遥感图像的混合像元分解,是一种简易可行的方法。

The mixed-pixels exist in the remote sensing images widely,and the decomposition of these mixed pixels is difficult and hot point of remote sensing images processing.This article uses supervisory FCM algorithm to decompose mixed pixels in remote sensing images.We introduce improved means to select the initial cluster centers combine with experiential knowledge based on the traditional FCM algorithm.We use simulative data which are produced by depressed sampling of ETM image,ETM and MODIS images to test its performance.The tests find that it is useful and easy to decomposition of mixed pixels in multi-spectrum remote sensing images.