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- W2113125088 abstract "Hyperspectral unmixing estimates the proportions of materials represented within a spectral signature. The over whelming majority of hyperspectral unmixing algorithms are based entirely on the spectral signatures of each individual pixel and do not incorporate the spatial information found in a hyperspectral data cube. In this work, a spectral unmixing algorithm, the Local Information Proportion estimation (LIP) algorithm, is presented. The proposed LIP algorithm incorporates spatial information while determining the proportions of materials found within a spectral signature. Spatial information is incorporated through the addition of a spatial term that regularizes proportion value estimates based on the weighted proportion values of neighboring pixels. Results are shown in the AVIRIS Indian Pines hyperspectral data set." @default.
- W2113125088 created "2016-06-24" @default.
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- W2113125088 date "2011-07-01" @default.
- W2113125088 modified "2023-10-18" @default.
- W2113125088 title "Spatial-spectral unmixing using fuzzy local information" @default.
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- W2113125088 doi "https://doi.org/10.1109/igarss.2011.6049398" @default.
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