Unsupervised Hyperspectral Unmixing via Nonlinear Autoencoders
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2021.3077833
Abstract: This work derives a novel unsupervised neural network-based scheme for unmixing hyperspectral pixels. A novel autoencoder structure was combined with a kernelization layer, mapping the mixed pixels in a higher dimensional space for easier separability,… read more here.
Keywords: structure; nonlinear mixing; unmixing via; via nonlinear ... See more keywords
Hyperspectral Sparse Unmixing via Nonconvex Shrinkage Penalties
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2022.3232570
Abstract: Hyperspectral sparse unmixing aims at finding the optimal subset of spectral signatures in the given spectral library and estimating their proportions in each pixel. Recently, simultaneously sparse and low-rank representations (SSLRRs) have been widely used… read more here.
Keywords: proposed framework; unmixing via; hyperspectral sparse; shrinkage ... See more keywords