Selecting and visualizing the spectral variability relevant for sample classification using principal component analysis
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Analytical Atomic Spectrometry"
DOI: 10.1039/d0ja00148a
Abstract: In this work we present a simple procedure based on principal component analysis (PCA) to reconstruct a measured spectrum by selecting the portion of its total variance of interest. We also provide an approach to… read more here.
Keywords: visualizing spectral; component analysis; spectral variability; principal component ... See more keywords
Characterizing the magnetic field and spectral variability of the rigidly rotating magnetosphere star HD 345439
Sign Up to like & getrecommendations! Published in 2017 at "Monthly Notices of the Royal Astronomical Society"
DOI: 10.1093/mnrasl/slx005
Abstract: A team involved in APOGEE, one of the Sloan Digital Sky Survey III programs, recently announced the discovery of two rare rigidly rotating magnetosphere stars, HD345439 and HD23478. Near-infrared spectra of these objects revealed emission-line… read more here.
Keywords: spectral variability; field; rotating magnetosphere; magnetic field ... See more keywords
Synthetic Hyperspectral Images With Controllable Spectral Variability and Ground Truth
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2022.3150245
Abstract: Spectral variability in hyperspectral images (HSIs) has received lot of attention over the last years, especially in the field of hyperspectral unmixing (HU) where it is a major issue. In this letter, we propose a… read more here.
Keywords: ground truth; variability; spectral variability; hyperspectral images ... See more keywords
Deep Generative Endmember Modeling: An Application to Unsupervised Spectral Unmixing
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Computational Imaging"
DOI: 10.1109/tci.2019.2948726
Abstract: Endmember (EM) spectral variability can greatly impact the performance of standard hyperspectral image analysis algorithms. Extended parametric models have been successfully applied to account for the EM spectral variability. However, these models still lack the… read more here.
Keywords: spectral unmixing; spectral variability; deep generative; model ... See more keywords
Hyperspectral Unmixing With Spectral Variability Using Adaptive Bundles and Double Sparsity
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2018.2889256
Abstract: Spectral variability is one of the major issues when conducting hyperspectral unmixing. Within a given image composed of some elementary materials (herein referred to as endmember classes), the spectral signatures characterizing these classes may spatially… read more here.
Keywords: hyperspectral unmixing; spectral variability; class; proposed method ... See more keywords
Hyperspectral Classification Through Unmixing Abundance Maps Addressing Spectral Variability
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2019.2892903
Abstract: Climate change and anthropogenic pressure are causing an indisputable decline in biodiversity; therefore, the need of environmental knowledge is important to develop the appropriate management plans. In this context, remote sensing and, specifically, hyperspectral imagery… read more here.
Keywords: classification unmixing; spectral variability; variability; hyperspectral classification ... See more keywords
Orthogonal Subspace Unmixing to Address Spectral Variability for Hyperspectral Image
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2023.3236471
Abstract: Hyperspectral unmixing aims at estimating pure spectral signatures and their proportions in each pixel. In practice, the atmospheric effects, intrinsic variation of the spectral signatures of the materials, illumination, and topographic changes cause what is… read more here.
Keywords: orthogonal subspace; address spectral; variability; subspace ... See more keywords
An Augmented Linear Mixing Model to Address Spectral Variability for Hyperspectral Unmixing
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Image Processing"
DOI: 10.1109/tip.2018.2878958
Abstract: Hyperspectral imagery collected from airborne or satellite sources inevitably suffers from spectral variability, making it difficult for spectral unmixing to accurately estimate abundance maps. The classical unmixing model, the linear mixing model (LMM), generally fails… read more here.
Keywords: spectral variability; linear mixing; address spectral; variability ... See more keywords