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Using FCMC, FVS, and PCA techniques for feature extraction of multispectral images

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5 Author(s)
Zhanli Sun ; Hefei Inst. of Intelligent Machines, Chinese Acad. of Sci., Anhui, China ; De-Shuang Huang ; Yiu-ming Cheung ; Jiming Liu
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In this letter, a new nonlinear approach based on a combination of the fuzzy c-means clustering (FCMC), feature vector selection and principal component analysis (PCA) is proposed to extract features of multispectral images when a very large number of samples need to be processed. The main contribution of this letter is to provide a preprocessing method for classifying these images with higher accuracy compared to the single PCA and kernel PCA. Finally, some experimental results demonstrate that our proposed approach is effective and efficient in analyzing multispectral images.

Published in:

Geoscience and Remote Sensing Letters, IEEE  (Volume:2 ,  Issue: 2 )

Date of Publication:

April 2005

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