Hyperspectral unmixing using deep convolutional autoencoder
Sign Up to like & getrecommendations! Published in 2020 at "International Journal of Remote Sensing"
DOI: 10.1080/01431161.2020.1724346
Abstract: ABSTRACT Hyperspectral Unmixing (HU) estimates the combination of endmembers and their corresponding fractional abundances in each of the mixed pixels in the hyperspectral remote sensing image. In this paper, we address the linear unmixing problem… read more here.
Keywords: unmixing using; deep convolutional; hyperspectral unmixing; convolutional autoencoder ... See more keywords
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