Results 111 to 120 of about 68,035 (215)

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, Gaetano Settembre, Nicolò Taggio, Flavia Esposito   +3 more
core   +1 more source

Updated Homogeneity Criteria Based Low-Dimensional Representation for Hyperspectral Unmixing

IEEE Access
Superpixel-based approaches have been proposed for hyperspectral unmixing. The basic assumption of this approach is that the superpixel over-segmentation segments the image into small homogeneous areas.
Jiarui Yi, Huiyi Gao
doaj   +1 more source

SCVolFormer: Spectral Consistency–Guided Volumetric Linear Self–Attention Transformer for Hyperspectral Unmixing

Photonics
Hyperspectral unmixing (HU) requires effective modeling of spectral–spatial information and local–global feature interactions to achieve accurate abundance estimation and endmember extraction.
Xinyu Cui, Xinyue Zhang, Da Sun, Aoran Dai   +3 more
doaj   +1 more source

Derivation of synthetic endmembers for linear unmixing to improve parameter estimation for soil erosion modelling in agricultural ecosystems. [PDF]

, 2007
Physically based erosion models have been widely accepted in soil erosion risk assessment in the past years but their application is still restricted due to a large disparity between required model input parameters and data availability.
Borg, Erik, Gerighausen, Heike
core  

A Global-to-Local Spectral-Spatial Attention-Based Nonlinearity and Scaled Endmember Variability Parametric Learning Network for Unmixing

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Hyperspectral unmixing has attracted increasing attention in remote sensing applications. Unfortunately, significant unmixing residuals often arise from the coupled nonlinear mixing effects and spectral variability (SV), bringing challenges for reliably ...
Yi Zhao, Bin Yang
doaj   +1 more source

Preprocessing Algorithm Leveraging Geometric Modeling for Scale Correction in Hyperspectral Images for Improved Unmixing Performance

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Spectral variability significantly impacts the accuracy and convergence of hyperspectral unmixing algorithms. Many methods address complex spectral variability; yet large-scale distortions to the scale of the observed pixel signatures due to topography ...
Praveen Sumanasekara, Athulya Ratnayake, Buddhi Wijenayake, Keshawa Ratnayake, Roshan Godaliyadda, Parakrama Ekanayake, Vijitha Herath   +6 more
doaj   +1 more source

A Deep Equilibrium Network for Hyperspectral Unmixing

CoRR
Hyperspectral unmixing (HU) is crucial for analyzing hyperspectral imagery, yet achieving accurate unmixing remains challenging. While traditional methods struggle to effectively model complex spectral-spatial features, deep learning approaches often lack physical interpretability.
Chentong Wang, Jincheng Gao, Fei Zhu, Jie Chen   +3 more
openaire   +3 more sources

Diffusion Model Based Hyperspectral Unmixing Using Spectral Prior Distribution

Hyperspectral unmixing is a crucial task for identifying the constituent materials and their respective distributions in a scene. Utilizing known spectral libraries as prior information, semi-blind unmixing methods (also known as spectral-library-based ...
Qian, Yuntao, Zhou, Jun, Deng, Keli, Nie, Jie   +3 more
core   +1 more source

Contributions to Hyperspectral Unmixing

Contribution au démélange hyperspectral Le démelangeage spectral est un domaine de recherche actif qui trouve des applications dans des domaines variés comme la télédétection, le traitement des signaux audio ou la chimie. Dans le contexte des capteurs hyper spectraux, les images acquises sont souvent de faible résolution spatiale ...
openaire   +2 more sources

An Open Evaluation of Hyperspectral Unmixing Strategies for EDS Analysis. [PDF]

Microsc Microanal, 2018
Taillon JA.
europepmc   +1 more source