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Remote Sensing Technology and Application  2006, Vol. 21 Issue (4): 288-293    DOI: 10.11873/j.issn.1004-0323.2006.4.288
article     
Study on Feature Selection and Extraction of Hyperspectral Data
SU Hong-jun1, 2, DU Pei-jun1
( 1. School of Environment Science and Spatial Informatics, China University of Mining and Technology ,
Xuzhou 221008, China; 2. Key Laboratory of Virtual Geographic Environment( Nanjing Normal University ) , Ministry of Education, Nanjing 210097, China)
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Abstract  

Because of the character of hyperspectral remote sensing data, it is necessary and urgent to develop hyperspectral data process algorithm. In this paper , some hyperspectral data process algorithms for feature selection and feature extraction was discussed, and its advantage & disadvantage was analyzed. In particular, we studied derivative spectral algorithm and put forward quad-encoding algorithm as the improved the binary encoding algorithm. Using the algorithms this paper proposed we extract spectral absorption parameter. The experiments have demonstrated that quad-encoding algorithm has the better performance than binary encoding on hyperspectral data, and for derivative spectrum it is effective to indicate
validate feature for objects when its rank is higher.

Key words:  Hyperspectral       Spectral feature      Feature selection and extraction      Objects recognition     
Received:  11 October 2005      Published:  27 September 2011
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SU Hong-jun, DU Pei-jun. Study on Feature Selection and Extraction of Hyperspectral Data. Remote Sensing Technology and Application, 2006, 21(4): 288-293.

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http://www.rsta.ac.cn/EN/10.11873/j.issn.1004-0323.2006.4.288     OR     http://www.rsta.ac.cn/EN/Y2006/V21/I4/288

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