[HTML][HTML] Deep learning in multimodal remote sensing data fusion: A comprehensive review

J Li, D Hong, L Gao, J Yao, K Zheng, B Zhang… - International Journal of …, 2022 - Elsevier
With the extremely rapid advances in remote sensing (RS) technology, a great quantity of
Earth observation (EO) data featuring considerable and complicated heterogeneity are …

Hyperspectral image super-resolution meets deep learning: A survey and perspective

X Wang, Q Hu, Y Cheng, J Ma - IEEE/CAA Journal of …, 2023 - ieeexplore.ieee.org
Hyperspectral image super-resolution, which refers to reconstructing the high-resolution
hyperspectral image from the input low-resolution observation, aims to improve the spatial …

X-shaped interactive autoencoders with cross-modality mutual learning for unsupervised hyperspectral image super-resolution

J Li, K Zheng, Z Li, L Gao, X Jia - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Hyperspectral image super-resolution (HSI-SR) can compensate for the incompleteness of
single-sensor imaging and provide desirable products with both high spatial and spectral …

Unsupervised deep tensor network for hyperspectral–multispectral image fusion

J Yang, L Xiao, YQ Zhao… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Fusing low-resolution (LR) hyperspectral images (HSIs) with high-resolution (HR)
multispectral images (MSIs) is a significant technology to enhance the resolution of HSIs …

Hyperspectral image super-resolution network based on cross-scale nonlocal attention

S Li, Y Tian, C Wang, H Wu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Hyperspectral image (HSI) super-resolution generally means the fusion of low-spatial-
resolution HSI (LRHSI) and high-spatial-resolution multispectral/panchromatic image …

MGDIN: Detail injection network for HSI and MSI fusion based on multiscale and global contextual features

C Zhu, L Gong, Y Zhang, S Chen, L Gao… - International Journal of …, 2023 - Taylor & Francis
Hyperspectral remote sensing images (HSI) are characterized as rich spectral information
with low spatial resolution, and a cost-effective way for the spatial information supplement is …

Model-guided deep unfolded fusion network with nonlocal spatial-spectral priors for hyperspectral image super-resolution

A Khader, J Yang, L Xiao - IEEE Journal of Selected Topics in …, 2023 - ieeexplore.ieee.org
Due to the physical boundaries, fusing low spatial resolution hyperspectral (LrHSI) with high
spatial resolution multispectral (HrMSI) images is a hot and promising area for obtaining …

Multispectral and hyperspectral image fusion based on low-rank unfolding network

J Yan, K Zhang, F Zhang, C Ge, W Wan, J Sun - Signal Processing, 2023 - Elsevier
Recently, deep unfolding networks (DUNs) have been applied to the fusion of low spatial
resolution hyperspectral (LR HS) and high spatial resolution multispectral (HR MS) images …

Crossed Dual-Branch U-Net for Hyperspectral Image Super-Resolution

J Zhang, J Liu, J Yang, Z Wu - IEEE Journal of Selected Topics …, 2023 - ieeexplore.ieee.org
Hyperspectral images have gained great achievements in many fields, but their low spatial
resolution limits the effectiveness in applications. Hyperspectral image super-resolution has …

Spatial-spectral unfolding network with mutual guidance for multispectral and hyperspectral image fusion

J Yan, K Zhang, Q Sun, C Ge, W Wan, J Sun… - Pattern Recognition, 2024 - Elsevier
Fusing low spatial resolution hyperspectral (LR HS) and high spatial resolution multispectral
(HR MS) images from different modalities aim to obtain high spatial resolution hyperspectral …