A novel NMF guided for hyperspectral unmixing from incomplete and noisy data
L Dong, X Lu, G Liu, Y Yuan - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The nonnegative matrix factorization (NMF)-combined spatial–spectral information has been
widely applied in the unmixing of hyperspectral images (HSIs). However, how to select the …
widely applied in the unmixing of hyperspectral images (HSIs). However, how to select the …
Graph-based blind hyperspectral unmixing via nonnegative matrix factorization
B Rathnayake, E Ekanayake… - … on Geoscience and …, 2020 - ieeexplore.ieee.org
Hyperspectral unmixing (HU) is a crucial step in the hyperspectral image (HSI) analysis. It
aims at decomposing the observed spectrum at each pixel into a collection of constituent …
aims at decomposing the observed spectrum at each pixel into a collection of constituent …
Constrained nonnegative matrix factorization for blind hyperspectral unmixing incorporating endmember independence
E Ekanayake, H Weerasooriya… - IEEE Journal of …, 2021 - ieeexplore.ieee.org
Hyperspectral unmixing (HU) has become an important technique in exploiting
hyperspectral data since it decomposes a mixed pixel into a collection of endmembers …
hyperspectral data since it decomposes a mixed pixel into a collection of endmembers …
[PDF][PDF] Mapping ilmenite deposit in Pulmudai, Sri Lanka using a hyperspectral imaging-based surface mineral mapping method.
E Ekanayake, SSP Vithana… - Journal of the …, 2019 - account.jnsfsl.sljol.info
Mineral detection using remote sensing techniques is important since it saves the time and
effort of carrying out manual land surveys. In this paper a novel algorithm, which can be …
effort of carrying out manual land surveys. In this paper a novel algorithm, which can be …
[HTML][HTML] Non-Negative Matrix Factorization with Averaged Kurtosis and Manifold Constraints for Blind Hyperspectral Unmixing
C Song, L Lu, C Zeng - Symmetry, 2024 - mdpi.com
The Nonnegative Matrix Factorization (NMF) algorithm and its variants have gained
widespread popularity across various domains, including neural networks, text clustering …
widespread popularity across various domains, including neural networks, text clustering …
[PDF][PDF] HYPERSPECTRAL IMAGE ANALYSIS FOR FEATURE DETECTION
ABSTRACT A hyperspectral image is a collection of images depicting the reflectance values
corresponding to a broad range of contiguous wavelengths. Feature detection using …
corresponding to a broad range of contiguous wavelengths. Feature detection using …