DocumentCode :
2812774
Title :
A framework to estimate natural classes in remotely sensed data
Author :
Prakash, H. N Srikanta ; Nagabhushan, P. ; Gowda, K. Chidananda
Author_Institution :
Dept. of Comput. Sci. & Eng., S.J. Coll. of Eng., Mysore, India
fYear :
1996
fDate :
18-20 Nov 1996
Firstpage :
264
Lastpage :
266
Abstract :
This paper presents a new approach to estimating the natural classes in remotely sensed data. The cluster index (CI) based on the mean difference index (MDI) concept for identifying the natural classes is proposed. This concept can be used in any classification procedures. In this paper, MDI uses the traditional symbolic ISODATA clustering algorithm to obtain the natural classes. The experimental results of multispectral IRS (Indian Remote Sensing) satellite data covering Mysore city, Karnataka State, India is encouraging. This endeavor is expected to open a new avenue in the area of CI for remotely sensed data
Keywords :
data analysis; geophysical techniques; geophysics computing; pattern classification; remote sensing; symbol manipulation; Indian Remote Sensing; classification; cluster index; experimental results; mean difference index; multispectral IRS; natural class estimation; remotely sensed data; satellite data; symbolic ISODATA clustering algorithm; Australia; Cities and towns; Clustering algorithms; Clustering methods; Data analysis; Educational institutions; Intelligent systems; Merging; Remote sensing; Satellites;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Information Systems, 1996., Australian and New Zealand Conference on
Conference_Location :
Adelaide, SA
Print_ISBN :
0-7803-3667-4
Type :
conf
DOI :
10.1109/ANZIIS.1996.573953
Filename :
573953
Link To Document :
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