DocumentCode
2730410
Title
Fast GPU algorithms for endmember extraction from hyperspectral images
Author
ElMaghrbay, Mahmoud ; Ammar, Reda ; Rajasekaran, Sanguthevar
Author_Institution
CSE Dept., Univ. of Connecticut, Storrs, CT, USA
fYear
2012
fDate
1-4 July 2012
Abstract
The N-FINDER algorithm is widely used for endmember extraction from hyperspectral images. One of the disadvantages of N-FINDER is that its sequential implementations have long run times due to their relatively large computational complexity. A fast parallel version of N-FINDER is developed in this paper. This version combined with the use of Hyperspectral Image Reduction for Endmember Extraction technique (HIREE) provides an algorithm that is 8 times faster than the original N-FINDER sequential algorithm.
Keywords
feature extraction; graphics processing units; image processing; HIREE; N-FINDER sequential algorithm; endmember extraction; fast GPU algorithm; hyperspectral image reduction; parallel version; Computational modeling; Data models; Graphics processing unit; Hyperspectral imaging; Instruction sets; Vectors; Endmember extraction; HIREE; Hyperspectral images; N-FINDER algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Computers and Communications (ISCC), 2012 IEEE Symposium on
Conference_Location
Cappadocia
ISSN
1530-1346
Print_ISBN
978-1-4673-2712-1
Electronic_ISBN
1530-1346
Type
conf
DOI
10.1109/ISCC.2012.6249368
Filename
6249368
Link To Document