Results 91 to 100 of about 3,939 (225)

FUSION OF HYPERSPECTRAL AND PANCHROMATIC IMAGES USING SPECTRAL UNMIXING RESULTS [PDF]

, 2013
Roozbeh Rajabi, Hassan Ghassemian
openalex   +1 more source

Spectral Variability Augmented Sparse Unmixing of Hyperspectral Images [PDF]

, 2022
Ge Zhang, Shaohui Mei, Bobo Xie, Mingyang Ma, Yifan Zhang, Yan Feng, Qian Du   +6 more
openalex   +1 more source

Application of spatially related MRF model in NMF hyperspectral unmixing [PDF]

, 2018
Bo Yuan
openalex   +1 more source

Learning Interpretable Deep Disentangled Neural Networks for Hyperspectral Unmixing [PDF]

, 2023
Ricardo Augusto Borsoi, Deniz Erdoğmuş, Tales Imbiriba   +2 more
openalex   +1 more source

Collaborative sparse regression using spatially correlated supports - Application to hyperspectral unmixing [PDF]

, 2014
Yoann Altmann, Marcelo Pereyra, José M. Bioucas‐Dias   +2 more
openalex   +1 more source

Inertia-Constrained Pixel-by-Pixel Nonnegative Matrix Factorisation: A Hyperspectral Unmixing Method Dealing with Intra-Class Variability [PDF]

, 2018
Charlotte Revel, Yannick Deville, Véronique Achard, Xavier Briottet, Christiane Weber   +4 more
openalex   +1 more source

GAUSS: Guided Encoder-Decoder Architecture for Hyperspectral Unmixing with Spatial Smoothness [PDF]

, 2022
Yasiru Ranasinghe, H.M.H.K. Weerasooriya, Roshan Godaliyadda, Vijitha Herath, Parakrama Ekanayake, Dhananjaya Jayasundara, Lakshitha Ramanayake, Neranjan Senarath, Dulantha Wickramasinghe   +8 more
openalex   +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

Towards Robust Hyperspectral Unmixing: Mixed Noise Modeling and Image-Domain Regularization [PDF]

, 2023
Kazuki Naganuma, Shunsuke Ono
openalex   +1 more source