Residual Dense Autoencoder Network for Nonlinear Hyperspectral Unmixing
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.2022.3188565
Abstract: Hyperspectral unmixing is a popular research topic in hyperspectral processing, aiming at obtaining the ground features contained in the mixed pixels and their proportion. Recently, nonlinear mixing models have received particular attention in hyperspectral decomposition… read more here.
Keywords: dense autoencoder; hyperspectral unmixing; autoencoder network; residual dense ... See more keywords
EndNet: Sparse AutoEncoder Network for Endmember Extraction and Hyperspectral Unmixing
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2018.2856929
Abstract: Data acquired from multichannel sensors are a highly valuable asset to interpret the environment for a variety of remote sensing applications. However, low spatial resolution is a critical limitation for previous sensors, and the constituent… read more here.
Keywords: extraction hyperspectral; hyperspectral unmixing; endmember extraction; autoencoder ... See more keywords