Title :
A layered sparse adaptive possibilistic approach for hyperspectral image clustering
Author :
Xenaki, Spyridoula D. ; Koutroumbas, Konstantinos D. ; Rontogiannis, Athanasios A. ; Sykioti, Olga A.
Author_Institution :
IAASARS, Nat. Obs. of Athens, Athens, Greece
Abstract :
In this paper a new algorithm suitable for hyperspectral image clustering, called L-SAPCM, is proposed. The algorithm works in layers where at each layer, after suitable pre-processing, the SAPCM clustering algorithm ([1]) is applied. Preliminary results on real hyperspectral images show enhanced performance compared to other related methods.
Keywords :
geophysical image processing; hyperspectral imaging; image enhancement; pattern clustering; L-SAPCM; SAPCM clustering algorithm; enhanced performance; hyperspectral image clustering; layered sparse adaptive possibilistic approach; real hyperspectral images; Clustering algorithms; Hyperspectral imaging; Roads; Soil; Vectors; Vegetation; hyperspectral; layered clustering; sparsity;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International
Conference_Location :
Quebec City, QC
DOI :
10.1109/IGARSS.2014.6947080
