DocumentCode :
2469388
Title :
Spatially-smooth piece-wise convex endmember detection
Author :
Zare, Alina ; Bchir, Ouiem ; Frigui, Hichem ; Gader, Paul
Author_Institution :
Dept. of Comput. & Inf. Sci. & Eng., Univ. of Florida, Gainesville, FL, USA
fYear :
2010
fDate :
14-16 June 2010
Firstpage :
1
Lastpage :
4
Abstract :
An endmember detection and spectral unmixing algorithm that uses both spatial and spectral information is presented. This method, Spatial Piece-wise Convex Multiple Model Endmember Detection (Spatial P-COMMEND), autonomously estimates multiple sets of endmembers and performs spectral unmixing for input hyperspectral data. Spatial P-COMMEND does not restrict the estimated endmembers to define a single convex region during spectral unmixing. Instead, a piece-wise convex representation is used that can effectively represent non-convex hyperspectral data. Spatial P-COMMEND drives neighboring pixels to be unmixed by the same set of endmembers encouraging spatially-smooth unmixing results.
Keywords :
computational geometry; geophysical image processing; object detection; endmember detection; nonconvex hyperspectral data; spatial information; spatial piece wise convex multiple model; spectral information; spectral unmixing algorithm; Data models; Equations; Hyperspectral imaging; Mathematical model; Pixel; Convex Geometry Model; Endmember; Fuzzy C-Means; Hyperspectral; Linear Mixing Model; Spatial; Spectral Unmixing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2010 2nd Workshop on
Conference_Location :
Reykjavik
Print_ISBN :
978-1-4244-8906-0
Electronic_ISBN :
978-1-4244-8907-7
Type :
conf
DOI :
10.1109/WHISPERS.2010.5594897
Filename :
5594897
Link To Document :
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