Title :
Comparative analysis of hyperspectral dimension reduction methods
Author :
Kozal, A.O. ; Teke, Mustafa ; Ilgin, H.A.
Author_Institution :
TUBITAK UZAY (Turkiye Bilimsel ve Teknolojik Arastirma Kurumu, Uzay Teknolojileri Arastirma Enstitusu), ODTU Yerleskesi, Ankara, Turkey
Abstract :
Hyperspectral sensors generate images in narrow bands in continuous manner with hundreds of spectral bands. The data with large number of bands require more processing power to classify. To decrease the redundancy in hyperspectral images and increase classifying efficiency with less number of bands, dimension reduction techniques are applied. In this paper, linear and non-linear dimension reduction methods are compared in classification performance and calculation time.
Keywords :
hyperspectral imaging; image classification; remote sensing; dimension reduction techniques; hyperspectral dimension reduction methods; hyperspectral images; hyperspectral sensors; narrow band image generation; nonlinear dimension reduction methods; spectral bands; Hyperspectral imaging; Image classification; Information processing; Measurement; Presses; Principal component analysis; dimension reduction; hyperspectral image classification; hyperspectral imaging; remote sensing;
Conference_Titel :
Signal Processing and Communications Applications Conference (SIU), 2013 21st
Conference_Location :
Haspolat
Print_ISBN :
978-1-4673-5562-9
Electronic_ISBN :
978-1-4673-5561-2
DOI :
10.1109/SIU.2013.6531487
