Title :
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
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;
Conference_Titel :
Computer Science and Software Engineering, 2008 International Conference on
Conference_Location :
Wuhan, Hubei
Print_ISBN :
978-0-7695-3336-0
DOI :
10.1109/CSSE.2008.1029
