Results 101 to 110 of about 9,243 (189)

Hyperspectral Unmixing With Multi-Scale Convolution Attention Network

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Hyperspectral unmixing is to decompose the mixed pixel into the spectral signatures (endmembers) with their corresponding abundances. However, the ignorance of endmember variability in hyperspectral unmixing results in low performance.
Sheng Hu, Huali Li
doaj   +1 more source

Tissue Classification of Breast Cancer by Hyperspectral Unmixing. [PDF]

Cancers (Basel), 2023
Jong LS, Post AL, Veluponnar D, Geldof F, Sterenborg HJCM, Ruers TJM, Dashtbozorg B.   +6 more
europepmc   +1 more source

A Multiple Hypothesis Testing Approach to Low-Complexity Subspace Unmixing [PDF]

, 2016
Subspace-based signal processing traditionally focuses on problems involving a few subspaces. Recently, a number of problems in different application areas have emerged that involve a significantly larger number of subspaces relative to the ambient ...
Bajwa, Waheed U., Mixon, Dustin G.
core  

Spectral-Spatial Hyperspectral Unmixing Using Multitask Learning

IEEE Access, 2019
Hyperspectral unmixing is an important and challenging task in the field of remote sensing which arises when the spatial resolution of sensors is insufficient for the separation of spectrally distinct materials.
Burkni Palsson, Johannes R. Sveinsson, Magnus O. Ulfarsson   +2 more
doaj   +1 more source

Non-Negative Matrix Factorization Based on Smoothing and Sparse Constraints for Hyperspectral Unmixing. [PDF]

Sensors (Basel), 2022
Jia X, Guo B.
europepmc   +1 more source

Object identification and characterization with hyperspectral imagery to identify structure and function of Natura 2000 habitats [PDF]

, 2010
Habitat monitoring of designated areas under the EU Habitats Directive requires every 6 years information on area, range, structure and function for the protected (Annex I) habitat types.
Delalieux, S., Haest, B., Kooistra, L., Mücher, C.A., Schmidt, A., Spanhove, T., Vanden Borre, J., Vermeulen, M.   +7 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

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

SCSU–GDO: Superpixel Collaborative Sparse Unmixing with Graph Differential Operator for Hyperspectral Imagery

Remote Sensing
In recent years, remarkable advancements have been achieved in hyperspectral unmixing (HU). Sparse unmixing, in which models mix pixels as linear combinations of endmembers and their corresponding fractional abundances, has become a dominant paradigm in ...
Kaijun Yang, Zhixin Zhao, Qishen Yang, Ruyi Feng   +3 more
doaj   +1 more source

Contributions to Hyperspectral Unmixing

, 2017
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, principalement à cause des limites technologiques liées aux ...
openaire   +1 more source