DocumentCode
299111
Title
Unsupervised, robust estimation-based clustering of remotely sensed images
Author
Netanyahu, Nathan S. ; Tilton, James C. ; Gualtieri, J. Anthony
Author_Institution
Center for Autom. Res., Maryland Univ., College Park, MD, USA
Volume
2
fYear
34881
fDate
10-14 Jul1995
Firstpage
1150
Abstract
Automated image clustering/classification is a task of considerable importance. To apply this task to remotely sensed imagery, the authors have pursued an unsupervised clustering scheme based on principles of robust (statistical) estimation. A description of the module employed and results obtained are provided
Keywords
geophysical signal processing; geophysical techniques; image classification; optical information processing; remote sensing; geophysical measurement technique; image classification; land surface; multispectral imaging; optical imaging; remote sensing; robust estimation-based clustering; terrain mapping; unsupervised clustering scheme; unsupervised image clustering; Automation; Clustering algorithms; Content management; Data mining; Educational institutions; Maximum likelihood estimation; NASA; Remote sensing; Robustness; Space technology;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing Symposium, 1995. IGARSS '95. 'Quantitative Remote Sensing for Science and Applications', International
Conference_Location
Firenze
Print_ISBN
0-7803-2567-2
Type
conf
DOI
10.1109/IGARSS.1995.521168
Filename
521168
Link To Document