Feature extraction and classification of hyperspectral remote sensing image oriented to easy mixed-classified objects  

作　　者：ZHANG Lian-peng~1, LIU Guo-lin~2, JIANG Tao~2 (1. Department of Territory Information and Surveying Engineering, Xuzhou Normal University, Xuzhou 221009, China 2. Shandong University of Science and Technology, Tai’an 271019,China) 

出　　处：《中国有色金属学会会刊：英文版》2005年第S1期168-171,共4页Transactions of Nonferrous Metals Society of China

基　　金：Project(40174003) supported by the National Natural Science Foundation of China

摘　　要：The classification of hyperspectral remote sensing data is an important problem theoretically and practically. With the increase of spectral bands, the separability of objects on remote sensing image should be improved. But the effects of traditional algorithm on feature extraction such as principal component analysis(PCA) is not so good for hyperspectral image. The key problem is that PCA can only represent the linear structure of data set; while the data clouds of different objects on hyperspectral image usually distribute on a nonlinear manifold. This paper established an algorithm of nonlinear feature extraction named as nonlinear principal poly lines, based on the algorithm, a classifier is constructed and the classification accuracy of hyperspectral image can be improved.The classification of hyperspectral remote sensing data is an important problem theoretically and practically. With the increase of spectral bands, the separability of objects on remote sensing image should be improved. But the effects of traditional algorithm on feature extraction such as principal component analysis(PCA) is not so good for hyperspectral image. The key problem is that PCA can only represent the linear structure of data set; while the data clouds of different objects on hyperspectral image usually distribute on a nonlinear manifold. This paper established an algorithm of nonlinear feature extraction named as nonlinear principal poly lines, based on the algorithm, a classifier is constructed and the classification accuracy of hyperspectral image can be improved.

关 键 词：HYPERSPECTRAL REMOTE sensing FEATURE extraction classification 

分 类 号：TP75[自动化与计算机技术—检测技术与自动化装置]