Results 101 to 110 of about 919,951 (170)
Adaptive Graph Regularized Multilayer Nonnegative Matrix Factorization for Hyperspectral Unmixing
, 2020 Hyperspectral unmixing is an important technique for remote sensing image analysis. Among various unmixing techniques, nonnegative matrix factorization (NMF) shows unique advantage in providing a unified solution with well physical interpretation.
Qian, Bin +4 more
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How hyperspectral image unmixing and denoising can boost each other
, 2020 : Hyperspectral linear unmixing and denoising are highly related hyperspectral image (HSI) analysis tasks. In particular, with the assumption of Gaussian noise, the linear model assumed for the HSI in the case of low-rank denoising is often the same as ...
Scheunders, Paul +7 more
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingHyperspectral unmixing (HU), an essential procedure for various environmental applications, has garnered significant attention within remote sensing communities. Among different groups of HU methods, nonnegative matrix factorization (NMF)-based ones have
Saeid Gholinejad, Alireza Amiri-Simkooei
doaj +1 more source
Superpixel-Based Nonnegative Tensor Factorization for Hyperspectral Unmixing
, 2018 Hyperspectral unmixing aims at decomposing a hyperspectral image (HSI) into a number of constituted materials and associated proportions. Recently, nonnegative tensor factorization (NTF) based methods have been proved effective and natural for ...
Jingzhou Chen +7 more
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A Theory-Guided Transformer for Interpretable Hyperspectral Unmixing
Remote SensingHyperspectral unmixing (HU) is fundamental for conducting quantitative analyses in remote sensing, yet existing methods face a persistent tradeoff between model performance and physical interpretability.
Hongyue Cao +4 more
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Deep NMF and Autoencoder: A Comparative Analysis for Hyperspectral Unmixing Using Prisma Real Images
In hyperspectral data, mixed pixels are frequent due to the low-medium spatial resolution of the imaging spectrometer, or to intimate mixing effects. Hence the process of blind hyperspectral unmixing, which separates the pixel spectra into a collection ...
Nicoletta Del Buono +3 more
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Hyperspectral unmixing via deep matrix factorization
, 2017 Hyperspectral unmixing is one of the most important techniques in hyperspectral remote sensing image analysis. During the past decades, many models have been widely used in hyperspectral unmixing, such as nonnegative matrix factorization (NMF) model ...
Chuangbai Xiao +3 more
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingThe purpose of hyperspectral unmixing (HU) is to extract the spectral signatures and their proportion fractions from the hyperspectral remote sensing image (HSIs), which is a crucial issue in HSIs processing.
Kewen Qu +4 more
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87th Annual Meeting of the Meteoritical Society 2025: Abstracts
Meteoritics &Planetary Science, Volume 60, Issue S1, Page 30-350, August 2025.
wiley +1 more source
Spatial-spectral collaborative attention network for hyperspectral unmixing
Geocarto InternationalIn recent years, the transformer architecture has demonstrated exceptional feature extraction capabilities in the field of computer vision (CV). Building on this, our paper aims to fully exploit the potential of the attention in transformers and apply it
Xiaojie Chen +3 more
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