Using FCMC, FVS, and PCA techniques for feature extraction of multispectral images |
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| Authors: | Zhan-Li Sun De-Shuang Huang Yiu-Ming Cheung Jiming Liu Guang-Bin Huang |
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| Institution: | Hefei Inst. of Intelligent Machines, Chinese Acad. of Sci., Anhui, China; |
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| Abstract: | 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. |
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