DocumentCode :
344241
Title :
Spectral angle automatic cluster routine (SAALT): an unsupervised multispectral clustering algorithm
Author :
Weisberg, Arel ; Najarian, Michelle ; Borowski, Brett ; Lisowski, Jim ; Miller, Bill
Author_Institution :
SciTec. Inc., Princeton, NJ, USA
Volume :
4
fYear :
1999
fDate :
1999
Firstpage :
307
Abstract :
The Spectral Angle Automatic cLuster rouTine (SAALT) algorithm consists of an iterative spectral angle calculator which seeks to cluster scenes captured with multispectral and hyperspectral imaging instruments. The unique aspect of SAALT is its ability to operate with little or no a priori information about the scene. SAALT has been applied to hyperspectral data that spans the visible and near infrared (IR) and to multispectral data that spans the visible, shortwave IR, and midwave IR. Both actual and simulated scenes were used in this study. The results demonstrate the capability of SAALT to divide a scene into its natural components, such as water, clouds, grass, trees, and roads. The utility of SAALT described in this paper is demonstrated with quick and successful differentiation between cloudy and clear pixels during day, night, dawn, and sunset scenes for a hypothetical multispectral remote sensing system
Keywords :
image segmentation; iterative methods; pattern clustering; remote sensing; SAALT; hyperspectral imaging instrument; iterative spectral angle calculation; multispectral remote sensing system; scene segmentation; spectral angle automatic cluster routine; unsupervised multispectral clustering algorithm; Algorithm design and analysis; Clouds; Clustering algorithms; Hyperspectral imaging; Hyperspectral sensors; Instruments; Iterative algorithms; Layout; Remote sensing; Roads;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Aerospace Conference, 1999. Proceedings. 1999 IEEE
Conference_Location :
Snowmass at Aspen, CO
Print_ISBN :
0-7803-5425-7
Type :
conf
DOI :
10.1109/AERO.1999.792099
Filename :
792099
Link To Document :
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