DocumentCode :
2677024
Title :
A spectral feature extraction algorithm for hyperspectral RS oil spill images
Author :
Gu, Ruidong ; Song, Meiping ; Lin, Bin ; An, Jubai
Author_Institution :
Dalian Maritime Univ., Dalian, China
fYear :
2012
fDate :
15-17 July 2012
Firstpage :
581
Lastpage :
585
Abstract :
The spectral curve´s feature is important for the nature analysis of the surface in hyperspectral remote sensing process. In this paper, a spectral curve feature extraction algorithm is proposed to deal with the classification of surface features. Several existing methods are compared with the new algorithm by testing the hyperspectral data sets which are obtained by experiments. The results show that the proposed algorithm can better describe the shape of the curve. The experiment on the actual hyperspectral images also shows the effectiveness of the algorithm.
Keywords :
feature extraction; geophysical image processing; hyperspectral imaging; image classification; oil pollution; remote sensing; set theory; spectral analysis; curve shape; hyperspectral RS oil spill images; hyperspectral data sets; hyperspectral remote sensing process; spectral curve feature; spectral feature extraction algorithm; surface feature classification; surface nature analysis; Algorithm design and analysis; Classification algorithms; Encoding; Feature extraction; Hyperspectral imaging; Vegetation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Information Processing (ICICIP), 2012 Third International Conference on
Conference_Location :
Dalian
Print_ISBN :
978-1-4577-2144-1
Type :
conf
DOI :
10.1109/ICICIP.2012.6391488
Filename :
6391488
Link To Document :
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