DocumentCode
2162792
Title
Blind analysis of hyperspectral images via Canonical Correlation Analysis
Author
Polat, Özgür Murat ; Özkazanç, Yakup
fYear
2012
fDate
18-20 April 2012
Firstpage
1
Lastpage
4
Abstract
Extraction of scene components is one of the main problems in the analysis of remotely sensed hyperspectral images. Scene components can be identified by applications of blind methods. In this study, two novel applications of Canonical Correlation Analysis (CCA) are proposed for the blind analysis of hyperspectral images.
Keywords
correlation methods; feature extraction; blind analysis; canonical correlation analysis; remotely sensed hyperspectral images; scene components extraction; Correlation; Hyperspectral imaging; Independent component analysis; Manganese; Principal component analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing and Communications Applications Conference (SIU), 2012 20th
Conference_Location
Mugla
Print_ISBN
978-1-4673-0055-1
Electronic_ISBN
978-1-4673-0054-4
Type
conf
DOI
10.1109/SIU.2012.6204741
Filename
6204741
Link To Document