Hyperspectral Remote Sensing Rock and Mineral Spectral Feature Mining Based on Rough Set Theory

Author

Zhan, Yunjun ; Hu, Guangdao ; Wu, Yanyan

Author_Institution

Inst. of Math. Geol. & Remote Sensing Geol., China Univ. of Geosci., Wuhan

Volume

4

fYear

2008

fDate

12-14 Dec. 2008

Firstpage

470

Lastpage

473

Abstract

The hyperspectral RS is a new technology for fine spectral feature, but the spectral feature of same class object are still not completely consistent, because the ground surface environment is complex. In this paper, we analyze the spectral characteristics and its fractal characteristics, and construct a spectrum curve feature matrix, which consist of center distance, informational entropy, fractal dimension, peak value, valley value, wavelength of the wave crests and two wave troughs. Then we apply the approximate classing of rough set theory to distinguish the rock and mineral from Hyperspectral image.

Keywords

curve fitting; data mining; entropy; feature extraction; fractals; fuzzy set theory; geophysical signal processing; image recognition; matrix algebra; remote sensing; rocks; rough set theory; spectral analysis; fractal dimension; fuzzy principle; hyperspectral remote sensing rock image; image identification; image processing; informational entropy; mineral spectral feature mining; rough set theory; spectrum curve feature matrix; Fractals; Hyperspectral imaging; Hyperspectral sensors; Information analysis; Minerals; Remote sensing; Rough surfaces; Set theory; Spectral analysis; Surface roughness; data mining; fractal; hyperspectral RS; rough set; spectral characteristic curve;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science and Software Engineering, 2008 International Conference on

Conference_Location

Wuhan, Hubei

Print_ISBN

978-0-7695-3336-0

Type

conf

DOI

10.1109/CSSE.2008.1029

Filename

4722660