SHEN Zhaoqing, SHU Ning, TAO Jianbin. An Algorithm of Weighted “1 V m” SVM Multi-classification for Hyperspectral Remote Sensing Image with NPA[J]. Geomatics and Information Science of Wuhan University, 2009, 34(12): 1444-1447.
Citation: SHEN Zhaoqing, SHU Ning, TAO Jianbin. An Algorithm of Weighted “1 V m” SVM Multi-classification for Hyperspectral Remote Sensing Image with NPA[J]. Geomatics and Information Science of Wuhan University, 2009, 34(12): 1444-1447.

An Algorithm of Weighted “1 V m” SVM Multi-classification for Hyperspectral Remote Sensing Image with NPA

Funds: 国家973计划资助项目(2006CB701303)
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  • Received Date: October 04, 2009
  • Revised Date: October 04, 2009
  • Published Date: December 04, 2009
  • According to the SVM computation theory and the features of hyperspectral remote sensing(RS) image data,the optimal hyperplane between two classes is computed by the nearest points algorithm(NPA).Reasonable weight indicators are designed for each class and a new weighted "1 V m" SVM based on NPA is proposed to achieve Hyperspectral RS image classification.The new algorithm can reduce the computational complexity and calculation of SVM,and improve SVM feasibilities and efficiencies for hyperspectral RS image classification.Finally,a test was carried out on OMIS image and good results are obtained.
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