LAUSR

About LAUSR
Donate
Contact Us

Follow us:

You are not signed in:

Sign Up!


   Articles with "sparse unmixing" as a keyword



A dual symmetric Gauss-Seidel alternating direction method of multipliers for hyperspectral sparse unmixing

Sign Up to like & get
recommendations! 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 & get
recommendations! 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

Spatial Structural Priors for Sparse Unmixing of Remotely Sensed Hyperspectral Images

Sign Up to like & get
recommendations! Published in 2025 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"

DOI: 10.1109/jstars.2025.3624109

Abstract: As spectral libraries continue to expand, sparse unmixing has become essential for effectively interpreting mixed pixels in remotely sensed hyperspectral data. Integrating spatial information into sparse unmixing is very important to enhance unmixing performance. However,… read more here.

Keywords: sparse; hyperspectral images; sparse unmixing; spatial structural ... See more keywords

SUnCNN: Sparse Unmixing Using Unsupervised Convolutional Neural Network

Sign Up to like & get
recommendations! 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 & get
recommendations! 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

Robust Sparse Unmixing via Continuous Mixed Norm to Address Mixed Noise

Sign Up to like & get
recommendations! Published in 2025 at "IEEE Geoscience and Remote Sensing Letters"

DOI: 10.1109/lgrs.2025.3548697

Abstract: Sparse unmixing, a critical task in hyperspectral image interpretation, aims to identify an optimal subset of endmembers from a predefined library and estimate the fractional abundances for each pixel. However, in real-world scenarios, various types… read more here.

Keywords: sparse; sparse unmixing; robust sparse; mixed noise ... See more keywords

A Comparison Between Three Sparse Unmixing Algorithms Using a Large Library of Shortwave Infrared Mineral Spectra

Sign Up to like & get
recommendations! 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 & get
recommendations! 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 & get
recommendations! 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

Sparse Unmixing in the Presence of Mixed Noise Using ℓ0-Norm Constraint and Log-Cosh Loss

Sign Up to like & get
recommendations! Published in 2024 at "IEEE Transactions on Geoscience and Remote Sensing"

DOI: 10.1109/tgrs.2024.3437346

Abstract: Over the past two decades, sparse unmixing (SU) has gained significant attention in the realm of hyperspectral imaging. The aims of SU are to seek a subset of spectral signatures and estimate their fractional abundances… read more here.

Keywords: sparse unmixing; tex math; inline formula;

Nonlocal weighted sparse unmixing based on global search and parallel optimization

Sign Up to like & get
recommendations! 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