Title :
Reducing the computation time of the Isodata and K-means unsupervised classification algorithms
Author :
Phillips, Steven
Author_Institution :
AT&T Labs.-Res., USA
Abstract :
Describes a sequence of methods to improve the running-time of the Isodata and K-means algorithms. The methods are compared on a range of remotely-sensed data sets, and show consistent and dramatic speedups.
Keywords :
image classification; remote sensing; unsupervised learning; Isodata algorithm; K-means algorithm; computation time; remotely-sensed data sets; unsupervised classification algorithms; Acceleration; Algorithm design and analysis; Classification algorithms; Image analysis; Image sensors; Pixel; Remote sensing; Satellites; Statistics; Testing;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2002. IGARSS '02. 2002 IEEE International
Print_ISBN :
0-7803-7536-X
DOI :
10.1109/IGARSS.2002.1026202
