An Unsupervised Classification Algorithm for Hyperspectral Imagery
一种无监督高光谱图像分类算法

In order to classify the data of Hyperspectral remote sensing images automatically without prior knowledge,an unsupervised classification algorithm is presented based on the conception of convex geometry and spectral features in this paper.The endmembers are selected step by step during processing and each endmember can be identified as one class.The advantages of this algorithm are simple in theory,easy to accomplish,widely used,and without any manual assistance.The experiment shows that the classifying result of this algorithm is satisfied.