In order to get interested images from vast Remote Sensing images, it is necessary to retrieve image based on content by using features in RS image.
为了从海量遥感影像库中提取需要的图象，必须应用影像本身具有的特征实施基于内容的遥感影像检索。
Shadow is one of the features in remote sensing image. It affects image matching, change detection or information extraction. But removing that is usually very hard in image processing.
阴影是遥感影像的基本特征之一，它将干扰图像匹配、图象变化检测或图像中信息的提取，而去除阴影则是遥感图像处理的难题。
In this paper, considering the features of remote sensing images, we proposed a remote sensing image classifier using radial basis function neural network.
针对遥感图象分类的特点，提出了一种径向基函数神经网络的遥感图象分类器。
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