光谱学与光谱分析 |
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The Multi-Spectra Classification Algorithm Based on K-Means Clustering and Spectral Angle Cosine |
WEI Jun-xia1,3,XIANGLI Bin2*,GAO Xiao-hui1,3,DUAN Xiao-feng1 |
1. Key Laboratory of Spectral Imaging Technology of Chinese Academy of Sciences, Laboratory of Spectral Imaging Technology, Xi’an Institute of Optics and Precision Mechanics, Xi’an 710119, China 2. Academy of Opto-Electronics, Chinese Academy of Sciences, Beijing 100190, China 3. Graduate University of Chinese Academy of Sciences, Beijing 100049, China |
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Abstract The classification and de-aliasing methods with respect to multi-spectra and hyper-spectra have been widely studied in recent years. And both K-mean clustering algorithm and spectral similarity algorithm are familiar classification methods. The present paper improved the K-mean clustering algorithm by using spectral similarity match algorithm to perform a new spectral classification algorithm. Two spectra with the farthest distance first were chosen as reference spectra. The Euclidean distance method or spectral angle cosine method then were used to classify data cube on the basis of the two reference spectra, and delete the spectra which belongs to the two reference spectra. The rest data cube was used to perform new classification according to a third spectrum, which is the farthest distance or the biggest angle one corresponding to the two reference spectra. Multi-spectral data cube was applied in the experimental test. The results of K-mean clustering classification by ENVI, compared with simulation results of the improved K-mean algorithm and the spectral angle cosine method, demonstrated that the latter two classify two air bubbles explicitly and effectively, and the improved K-mean algorithm classifies backgrounds better, especially the Euclidean distance method can classify the backgrounds integrally.
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Received: 2010-06-29
Accepted: 2010-09-08
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Corresponding Authors:
XIANGLI Bin
E-mail: xiangli@opt.cn
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[1] HAN Jiawei,Micheline Kambe-Data Mining. Concepts and Techniques. Beijing: Higher Education Publishing Company,Morgan Kaufmann Publishers,2001. [2] WANG Yu(王 宇),Computer Engineering and Design(计算机工程与设计),2004,25(11):1884. [3] Han J, Kamber M. Data Mining Concepts and Techniques. Beijing: China Machine Press, 2001. 232. [4] XU Yi-feng, CHEN Chun-ming, XU Yun-qing(徐义峰, 陈春明, 徐云青). Computer Applications and Software(计算机应用与软件),2008,25(3):275. [5] LIU Jing-ming, HAN Li-chuan, HOU Li-wen(刘靖明, 韩丽川, 侯立文). Systems Engineering Theory and Practice(系统工程理论与实践),2005, (6):54. [6] Zhang Sunstone. wenku.baidu.com(百度文库). Clustering Arithmetic Summarize. [7] ZHANG Jian-min(张建民). Mini-Computer Information(微计算机信息),2010,126(3):233. [8] Suebsing Anirut. Proceedings-2009 1st Asian Conference on Intelligent Information and Database System, ACIIDS, 2009, 86. [9] SONG Yu-chen, ZHANG Yu-ying, MENG Hai-dong(宋宇辰,张玉英,孟海东). Computer Engineering and Applications(计算机工程与应用),2007,143(4):179. [10] Landgrebe D, Biehl L. (2001) An Introduction to MultiSpec, School of Electrical and Computer Engineering, Purdue University, USA, Available at: http://www.ece.purdue.edu/~biehl/MultiSpec/Intro5_01.pdf.
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