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| Hyperspectral Band Reduction Based on Rough Sets and Fuzzy C-Means Clustering |
| Shi Hong; Shen Yi; Liu Zhi-yan |
| Dept of Control Eng.,Harbin Institute of Technology Harbin 150001 China |
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Abstract A method of hyperspectral baud reduction based on Rough Sets (RS) and Fuzzy C-Means (FCM) clustering is proposed, which consists of the following two steps. First, Fuzzy C-Means clustering algorithm is used to classify the original bands into equivalent band groups, which employs the concept of attribute dependency defined in RS to define the distance between a group and the cluster center, viz. the correlatives of adjacent bands. Then the data is reduced by selecting the only one from each group with maximum grade of fuzzy membership. With this approach, great dimension of band is decreased while preserving much wanted information. Simulation results prove the effectiveness of this approach.
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Received: 13 December 2002
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2004, Vol. 26 
