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
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;
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
DOI :
10.1109/IGARSS.1995.521168
