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As a result of the spatial consideration of the imagery, spatial sparse unmixing (SU) can improve the unmixing accuracy for hyperspectral imagery, based on the application of a spectral library and sparse representation. To better utilize the spatial information, spatial SU methods such as SU via variable splitting augmented Lagrangian and total variation (SUnSAL-TV) and nonlocal SU (NLSU) have been...
Spatial sparse unmixing techniques have been known as a series of effective way in improving the unmixing accuracy with the integration of spatial correlations of imagery. To better utilize the non-local spatial information, spatial sparse unmixing methods based on non-local means such as nonlocal sparse unmixing (NLSU) have been proposed. However, the non-local spatial correlations in NLSU represented...
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