Spatial-Aware Hyperspectral Nonlinear Unmixing Autoencoder With Endmember Number Estimation
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.2021.3132283
Abstract: In this article, we develop a novel fully unsupervised autoencoder-based scheme for nonlinear hyperspectral pixel unmixing. A unique approach is derived where high noise and unresponsive pixels are accounted for, by a unique averaging approach… read more here.
Keywords: spatial aware; autoencoder; number; estimation ... See more keywords
Hyperspectral Shadow Removal via Nonlinear Unmixing
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2020.2987353
Abstract: Removing shadows that are often present in remotely sensed hyperspectral images is important for both enhancing the interpretability of the data and further target analysis. Shadow removal approaches based on spectral unmixing have been proposed… read more here.
Keywords: unmixing hyperspectral; removal; nonlinear unmixing; shadow removal ... See more keywords
Reweighted Kernel-Based Nonlinear Hyperspectral Unmixing With Regional ℓ₁-Norm Regularization
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DOI: 10.1109/lgrs.2021.3083403
Abstract: Improving the performance of nonlinear unmixing has become an active topic among the remote sensing applications. Usually, the noise levels of hyperspectral images (HSIs) vary with different bands. However, this fact is generally ignored and… read more here.
Keywords: kernel based; nonlinear unmixing; based nonlinear; different bands ... See more keywords
Using Low-Rank Representation of Abundance Maps and Nonnegative Tensor Factorization for Hyperspectral Nonlinear Unmixing
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2021.3065990
Abstract: Tensor-based methods have been widely studied to attack inverse problems in hyperspectral imaging since a hyperspectral image (HSI) cube can be naturally represented as a third-order tensor, which can perfectly retain the spatial information in… read more here.
Keywords: abundance maps; low rank; nonlinear unmixing; tensor ... See more keywords
Nonlinear Unmixing for Hyperspectral Images via Kernel-Transformed Bilinear Mixing Models
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DOI: 10.1109/tgrs.2021.3135571
Abstract: Due to the presence of multiple scatterings, linear unmixing methods may not perform well in practical applications, and thus nonlinear unmixing has become an urgent problem to be solved. Usually, the mixing process in the… read more here.
Keywords: kernel transformed; nonlinear unmixing; mixing models; bilinear mixing ... See more keywords
Supervised Nonlinear Hyperspectral Unmixing with Automatic Shadow Compensation using Multi-swarm Particle Swarm Optimization
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2022.3177648
Abstract: The presence of shadows has always been a troublesome problem in image processing and can also affect spectral unmixing with hyperspectral remote sensing images. Traditional unmixing algorithms regard shadows as a special type of ground… read more here.
Keywords: optimization; swarm optimization; particle swarm; nonlinear unmixing ... See more keywords