Hyperspectral unmixing

Hyper-spectral unmixing is a technique to estimate the abundances of different endmembers in each mixed pixel of remote sensing images. Deep learning has made significant progress in this area, offering automatic feature extraction, nonlinear pattern recognition, and end-to-end solutions. However, existing deep learning models have not fully utilized the spectral information of endmembers, leading to insufficient data mining.