Results 91 to 100 of about 828,208 (170)
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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Spectral Mixture Model Inspired Network Architectures for Hyperspectral Unmixing
, 2020 In many statistical hyperspectral unmixing approaches, the unmixing task is essentially an optimization problem given a defined linear or nonlinear spectral mixture model. However, most of the model inference algorithms require a time-consuming iterative
Qian, Qipeng +3 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
doaj +1 more source
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
core +1 more source
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
doaj +1 more source
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
doaj +1 more source
Efficient Progressive Mamba Model for Hyperspectral Sequence Unmixing
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingIn recent years, deep learning-based hyperspectral unmixing has increasingly incorporated spatial information to improve performance. However, the extent of spatial information introduced involves a complex tradeoff: too little offers limited gains ...
Yang Liu, Shujun Liu, Huajun Wang
doaj +1 more source
Hyperspectral Unmixing Using Frequency-Adaptive Convolutional-Mamba Network
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingIn recent years, deep learning (DL) has achieved remarkable progress in hyperspectral unmixing (HU) owing to its powerful feature extraction and modeling capabilities.
Zhuoyi Zhao +5 more
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingHyperspectral unmixing (HU) aims to extract the pure material spectra (endmember) and their corresponding fractions (abundances) from the mixed pixels.
Kewen Qu +4 more
doaj +1 more source