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 +6 more
doaj +1 more source
Low-Rank Tensor Modeling for Hyperspectral Unmixing Accounting for\n Spectral Variability [PDF]
Tales Imbiriba +2 more
openalex +1 more source
The Spatial LASSO With Applications to Unmixing Hyperspectral Biomedical Images
Daniel V. Samarov +2 more
openalex +1 more source
Model-Based Deep Autoencoder Networks for Nonlinear Hyperspectral Unmixing [PDF]
Haoqing Li +5 more
openalex +1 more source
Spectral unmixing approach in hyperspectral remote sensing: a tool for oil palm mapping
Héctor Vargas +2 more
openalex +2 more sources
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
Endmember-Guided Unmixing Network (EGU-Net): A General Deep Learning Framework for Self-Supervised Hyperspectral Unmixing [PDF]
Danfeng Hong +6 more
openalex +1 more source
A Dye-Free Analog to Retinal Angiography Using Hyperspectral Unmixing to Retrieve Oxyhemoglobin Abundance. [PDF]
Dwight JG +3 more
europepmc +1 more source
Ground Truth Simulation for Deep Learning Classification of Mid-Resolution Venus Images Via Unmixing of High-Resolution Hyperspectral Fenix Data [PDF]
Ido Faran +6 more
openalex +1 more source
Improved Hyperspectral Unmixing with Endmember Variability Parametrized Using an Interpolated Scaling Tensor [PDF]
Ricardo Augusto Borsoi +2 more
openalex +1 more source

