高分辨率遥感数据处理方法实验研究

Experimental study of methods for high spatial resolution remote sensing data processing

近几年高分辨率遥感数据处理与应用研究越来越受到国内外学者的重视,已成为目前遥感应用研究领域的热点和难点之一。首先分析了基于像素的中分辨率卫星数据的遥感数据处理方法,包括:基于统计理论的分类方法和基于光谱信息的非参数理论方法的分类方法。在此基础上,针对高分辨率遥感图像的特点,分析了面向对象的高分辨率遥感数据处理方法。其中,图像分割是最关键的一步,即如何有效地提取出对象特征非常重要。最后,给出了高分辨率遥感数据处理方法相关算法实验,主要进行了几种图像分割算法实验,同时结合植被变化检测,进行了变化检测算法实验。

The processing of high spatial resolution remote sensing （HSRRS） data has become a major focus in the remote sensing field since the 1999s. In this paper, firstly we have analyzed the processing methods based on pixels of moderate spatial resolution remote sensing （MSRRS） data, including the classification methods based on statistics theory and the classification methods based on nonparametric theory. Secondly, we have made the analysis of processing methods based on objects of HSRRS data according to the image feature of HSRRS data. Image segmentation, i.e. , how to extract the features of objects effectively, is the key of HSRRS data processing methods. Finally, we have carried out some experiments of HSRRS data processing methods, and studied several image segmentation methods of HSRRS data. According to the application of vegetation changes detection, the experiments of the vegetation change detection using HSRRS data are introduced.