Title :
A fuzzy partitioning method of spectral space for remote sensing image classification
Author :
Kim, Jin-Il ; Kim, Sung-Chun
Author_Institution :
Dept. of Comput. Eng., Dongeui Univ., Pusan, South Korea
Abstract :
The aim of this study is to propose an efficient method for partition of spectral space into fuzzy subspace for multi-spectral remote sensing image. The suggested method predicates on sequential subdivision of the fuzzy subspace, and the size of constructed fuzzy space is variable. Under this procedure, n-dimensional pattern space, after considering the distributional characteristic patterns, is partitioned into two different fuzzy subspaces. From the two fuzzy subspaces, the pattern space for further subdivision is chosen; then, this subdivision procedure recursively repeats itself until the stopping condition is fulfilled. The result of this study is applied to 2, 4, 7 band of satellite Landsat TM and satisfactory result is acquired
Keywords :
fuzzy set theory; geophysical signal processing; geophysical techniques; image classification; optical information processing; remote sensing; spectral analysis; Landsat TM; fuzzy partitioning method; fuzzy subspace; geophysical measurement technique; land surface terrain mapping; multidimensional pattern space; multispectral remote sensing image; optical imaging; remote sensing; remote sensing image classification; sequential subdivision; spectral space; Application software; Artificial neural networks; Computer science; Fuzzy logic; Fuzzy set theory; Image classification; Pixel; Remote sensing; Satellites; Statistics;
Conference_Titel :
Fuzzy Systems, 1995. International Joint Conference of the Fourth IEEE International Conference on Fuzzy Systems and The Second International Fuzzy Engineering Symposium., Proceedings of 1995 IEEE Int
Conference_Location :
Yokohama
Print_ISBN :
0-7803-2461-7
DOI :
10.1109/FUZZY.1995.409824