摘要
As a new remote sensing technology,the hypersperctral technique is still in an exploring stage in our country. On the basis of hyperspectral remote sensing image processing,this paper studies the classification and recognition of the Cuprite ore district of the U.S. in view of pixel statistics and spectrum characters,and extracts the information of eight kinds of rocks and ores,and assesses the classification accuracies for different classification methods using confusion matrix. The results show that the more concentrated spatial distribution of rocks and minerals exhibits,the more obvious spectrum characters,and the higher classification accuracy. The classification methods based on the spectral characteristics is better than that based on the traditional statistical analysis. This provides a theoretical basis for mineral mapping using the hyperspectral remote sensing technology.