Hyperspectral feature recognition based on kernel PCA and relational perspective map |
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| Authors: | Hongjun Su Yehua Sheng Key Laboratory of Virtual Geographic Environment Nanjing Normal University Nanjing China |
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| Institution: | Hongjun Su and Yehua Sheng Key Laboratory of Virtual Geographic Environment(Ministry of Education),Nanjing Normal University,Nanjing 210046,China |
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| Abstract: | A novel joint kernel principal component analysis(PCA) and relational perspective map(RPM) method called KPmapper is proposed for hyperspectral dimensionality reduction and spectral feature recognition. Kernel PCA is used to analyze hyperspectral data so that the major information corresponding to features can be better extracted.RPM is used to visualize hyperspectral data through two-dimensional(2D) maps, and it is an efficient approach to discover regularities and extract information by partitioning the d... |
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