A dual symmetric Gauss-Seidel alternating direction method of multipliers for hyperspectral sparse unmixing
Sign Up to like & getrecommendations! Published in 2020 at "Numerical Algorithms"
DOI: 10.1007/s11075-020-00985-8
Abstract: Since sparse unmixing has emerged as a promising approach to hyperspectral unmixing, some spatial-contextual information in the hyperspectral images has been exploited to improve the performance of the unmixing recently. The total variation (TV) has… read more here.
Keywords: alternating direction; direction method; hyperspectral sparse; sparse unmixing ... See more keywords
Centralized Collaborative Sparse Unmixing for Hyperspectral Images
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2017.2651063
Abstract: Spectral unmixing is very important in hyperspectral image analysis and processing, which aims at identifying the constituent spectra (i.e., endmembers) and estimating their fractional abundances from the mixed pixels. In recent years, sparse unmixing has… read more here.
Keywords: abundance estimation; sparse unmixing; collaborative sparse; hyperspectral images ... See more keywords
SUnCNN: Sparse Unmixing Using Unsupervised Convolutional Neural Network
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2021.3100992
Abstract: In this letter, we propose a sparse unmixing technique using a convolutional neural network (SUnCNN) for hyperspectral images. SUnCNN is the first deep learning-based technique proposed for sparse unmixing. It uses a deep convolutional encoder–decoder… read more here.
Keywords: neural network; network; sparse; convolutional neural ... See more keywords
Unsupervised Sparse Unmixing of Atmospheric Trace Gases From Hyperspectral Satellite Data
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2022.3141551
Abstract: In this letter, a new approach for the retrieval of the vertical column concentrations of trace gases from hyperspectral satellite observations is proposed. The main idea is to perform a linear spectral unmixing by estimating… read more here.
Keywords: trace gases; gases hyperspectral; unsupervised sparse; sparse unmixing ... See more keywords
A Comparison Between Three Sparse Unmixing Algorithms Using a Large Library of Shortwave Infrared Mineral Spectra
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2017.2676816
Abstract: The comparison described in this paper has been motivated by two things: 1) a “spectral library” of shortwave infrared reflectance spectra that we have built, consisting of the spectra of 60 nominally pure materials (mostly… read more here.
Keywords: algorithms using; shortwave infrared; sparse unmixing; library shortwave ... See more keywords
Reweighted Low-rank and Joint-sparse Unmixing With Library Pruning
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2022.3168932
Abstract: Sparse unmixing is a semi-supervised learning problem, which performs abundance estimation when a spectral library is given. In this way, the essence of sparse unmixing is to select the most suitable subset from the spectral… read more here.
Keywords: sparse; low rank; sparse unmixing; joint sparse ... 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
Nonlocal weighted sparse unmixing based on global search and parallel optimization
Sign Up to like & getrecommendations! Published in 2021 at "Journal of Applied Remote Sensing"
DOI: 10.1117/1.jrs.15.016501
Abstract: Abstract. Sparse unmixing (SU) can represent an observed image using pure spectral signatures and corresponding fractional abundance from a large spectral library and is an important technique in hyperspectral unmixing. However, the existing SU algorithms… read more here.
Keywords: based global; global search; nonlocal weighted; sparse unmixing ... See more keywords