遥感数据的粗糙集表示及分类

Classification and Presentation of Remote Sensing Data on Rough Set

由于粗糙集理论对不确定性的描述是相对客观的,且在无需先验信息的情况下提供了严格地处理数据分类问题的数学方法,结合遥感数据的不确定性,就能对遥感数据进行分类处理。文章通过对遥感数据的处理,经过数据离散化等一系列数据处理后得到约简属性,再根据Fisher线性判别对遥感数据进行监督分类,得到分类结果。可以得出粗糙集理论应用于遥感数据分类具有良好的应用前景。

Because of rough set theory to the description of uncertainty is relatively objective, and provided a rigorous classification of data to deal with the issue of mathematical methods without a priori information. Combined with the uncertainty of remote sensing data, the classification of remote sensing data could be done. In the paper, through the processing of remote sensing data, for example, data discretization and so on, attribute reduction could be got. According to Fisher Linear Discriminant to supervised classification of remote sensing data, then the classification results could be gained. So the results show that rough set theory can be applied to the classification of remote sensing data, and has a good application prospects.