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- W2118945875 abstract "Feature extraction is an necessary preprocessing step for information extraction from hyperspectral remote sensing data. We exploit locality preserving projections (LPP) for dimensionality reduction, leading to a low-dimensional embedding. Given a subset of hyperspectral image, by LPP, we project them into a low-dimensional space to preserve much of the geometric structure. Hyperspectral image classification is then achieved using Support Vector Machine. To evaluate the proposed method, LPP method was examined in terms of spatial information preservation. The preliminary result of this study demonstrated that it is effective." @default.
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- W2118945875 date "2011-06-01" @default.
- W2118945875 modified "2023-09-26" @default.
- W2118945875 title "Locality perserving projections algorithm for hyperspectral image dimensionality reduction" @default.
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- W2118945875 doi "https://doi.org/10.1109/geoinformatics.2011.5980790" @default.
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