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A new object-oriented mapping approach is proposed based on nonlinear subspace feature analysis of hyperspectral data. A nonlinear manifold learning approach ISOMAP were utilized to obtain subspace feature representation of hyperspectral remote sensing imagery. Afterwards, the extracted subspace feature images were fed into the object-oriented system. Multiresolution segmentation algorithm was utilized...
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