Nonnegative Matrix Factorization With Data-Guided Constraints For Hyperspectral Unmixing
Author:
Publisher
MDPI AG
Subject
General Earth and Planetary Sciences
Link
http://www.mdpi.com/2072-4292/9/10/1074/pdf
Reference44 articles.
1. Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches
2. Unsupervised Post-Nonlinear Unmixing of Hyperspectral Images Using a Hamiltonian Monte Carlo Algorithm
3. Robust Hyperspectral Unmixing With Correntropy-Based Metric
4. Unsupervised Nonlinear Spectral Unmixing Based on a Multilinear Mixing Model
5. Matrix-Vector Nonnegative Tensor Factorization for Blind Unmixing of Hyperspectral Imagery
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1. Robust Hyperspectral Unmixing with Practical Learning-Based Hyperspectral Image Denoising;Remote Sensing;2023-02-15
2. Non-Negative Matrix Factorization Based on Smoothing and Sparse Constraints for Hyperspectral Unmixing;Sensors;2022-07-20
3. Simulation of an Algorithm for Space Target Materials Identification Based on vis-NIR Hyperspectral Data;Spectroscopy;2022-07-01
4. Hyperspectral Unmixing Based on Nonnegative Matrix Factorization: A Comprehensive Review;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2022
5. Correntropy-Based Spatial-Spectral Robust Sparsity-Regularized Hyperspectral Unmixing;IEEE Transactions on Geoscience and Remote Sensing;2021-02
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