Title :
An unsupervised algorithm for the selection of endmembers in hyperspectral images
Author :
Acito, N. ; Corsini, G. ; Diani, M.
Author_Institution :
Dipt. di Ingegneria dell´´Informazione, Pisa Univ., Italy
Abstract :
An efficient algorithm for endmember selection is illustrated. Endmembers are estimated by an unsupervised segmentation procedure based on spectral analysis. Preliminary results obtained on experimental data are presented and discussed.
Keywords :
geophysical signal processing; geophysical techniques; image processing; image segmentation; multidimensional signal processing; remote sensing; terrain mapping; vegetation mapping; 400 to 2500 nm; IR; endmember selection; endmembers; geophysical measurement technique; hyperspectral images; hyperspectral remote sensing; image processing; infrared; land surface; multidimensional signal processing; multispectral remote sensing; spectral analysis; terrain mapping; unsupervised algorithm; unsupervised segmentation; vegetation mapping; visible; Background noise; Covariance matrix; Histograms; Hyperspectral imaging; Image segmentation; Layout; Principal component analysis; Spatial resolution; Spectral analysis; Vectors;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2002. IGARSS '02. 2002 IEEE International
Print_ISBN :
0-7803-7536-X
DOI :
10.1109/IGARSS.2002.1026217
