A geometric modeling-based preprocessing algorithm corrects scale variability in hyperspectral images prior to unmixing, yielding around 50% error reduction in abundance estimation across multiple algorithms on synthetic and real datasets.
SSAF-Net: A Spatial-Spectral Adaptive Fusion Network for Hyperspectral Unmixing with Endmember Variability,
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Preprocessing Algorithm Leveraging Geometric Modeling for Scale Correction in Hyperspectral Images for Improved Unmixing Performance
A geometric modeling-based preprocessing algorithm corrects scale variability in hyperspectral images prior to unmixing, yielding around 50% error reduction in abundance estimation across multiple algorithms on synthetic and real datasets.