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- W2046205311 abstract "In this paper, we develop a new spatial preprocessing strategy which can be applied prior to a spectral-based endmember extraction process for unmixing of hyperspectral data. Our proposed approach directs the endmember searching process to regions which are both spectrally pure and spatially homogeneous in the scene. Our experimental results, conducted using simulated hyperspectral data sets with known endmembers and fractional abundances, reveal that the proposed approach can successfully integrate the spatial and spectral information in the search for more relevant endmembers." @default.
- W2046205311 created "2016-06-24" @default.
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- W2046205311 date "2010-07-01" @default.
- W2046205311 modified "2023-09-24" @default.
- W2046205311 title "Spatial preprocessing for endmember extraction using unsupervised clustering and orthogonal subspace projection concepts" @default.
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- W2046205311 doi "https://doi.org/10.1109/igarss.2010.5649341" @default.
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