Blind Hyperspectral Unmixing Using Autoencoders: A Critical Comparison
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2021.3140154
Abstract: Deep learning (DL) has heavily impacted the data-intensive field of remote sensing. Autoencoders are a type of DL methods that have been found to be powerful for blind hyperspectral unmixing (HU). HU is the process… read more here.
Keywords: critical comparison; using autoencoders; unmixing using; blind hyperspectral ... See more keywords
Blind Hyperspectral Unmixing Considering the Adjacency Effect
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2019.2907567
Abstract: This paper focuses on the blind unmixing technique for analyzing hyperspectral images (HSIs). A joint deconvolution and blind hyperspectral unmixing (DBHU) algorithm is proposed, which is aimed at eliminating the impact of the adjacency effect… read more here.
Keywords: adjacency effect; hyperspectral unmixing; problem; blind hyperspectral ... See more keywords