[HTML][HTML] Deep learning in multimodal remote sensing data fusion: A comprehensive review
With the extremely rapid advances in remote sensing (RS) technology, a great quantity of
Earth observation (EO) data featuring considerable and complicated heterogeneity are …
Earth observation (EO) data featuring considerable and complicated heterogeneity are …
A new benchmark based on recent advances in multispectral pansharpening: Revisiting pansharpening with classical and emerging pansharpening methods
Pansharpening refers to the fusion of a multispectral (MS) image and panchromatic (PAN)
data aimed at generating an outcome with the same spatial resolution of the PAN data and …
data aimed at generating an outcome with the same spatial resolution of the PAN data and …
Multispectral and hyperspectral image fusion in remote sensing: A survey
G Vivone - Information Fusion, 2023 - Elsevier
The fusion of multispectral (MS) and hyperspectral (HS) images has recently been put in the
spotlight. The combination of high spatial resolution MS images with HS data showing a …
spotlight. The combination of high spatial resolution MS images with HS data showing a …
Hypertransformer: A textural and spectral feature fusion transformer for pansharpening
WGC Bandara, VM Patel - … of the IEEE/CVF conference on …, 2022 - openaccess.thecvf.com
Pansharpening aims to fuse a registered high-resolution panchromatic image (PAN) with a
low-resolution hyperspectral image (LR-HSI) to generate an enhanced HSI with high …
low-resolution hyperspectral image (LR-HSI) to generate an enhanced HSI with high …
Spatial-frequency domain information integration for pan-sharpening
Pan-sharpening aims to generate high-resolution multi-spectral (MS) images by fusing PAN
images and low-resolution MS images. Despite its great advances, most existing pan …
images and low-resolution MS images. Despite its great advances, most existing pan …
Machine learning in pansharpening: A benchmark, from shallow to deep networks
Machine learning (ML) is influencing the literature in several research fields, often through
state-of-the-art approaches. In the past several years, ML has been explored for …
state-of-the-art approaches. In the past several years, ML has been explored for …
Detail injection-based deep convolutional neural networks for pansharpening
The fusion of high spatial resolution panchromatic (PAN) data with simultaneously acquired
multispectral (MS) data with the lower spatial resolution is a hot topic, which is often called …
multispectral (MS) data with the lower spatial resolution is a hot topic, which is often called …
Hyperspectral image super-resolution via deep spatiospectral attention convolutional neural networks
Hyperspectral images (HSIs) are of crucial importance in order to better understand features
from a large number of spectral channels. Restricted by its inner imaging mechanism, the …
from a large number of spectral channels. Restricted by its inner imaging mechanism, the …
Deep learning for pixel-level image fusion: Recent advances and future prospects
By integrating the information contained in multiple images of the same scene into one
composite image, pixel-level image fusion is recognized as having high significance in a …
composite image, pixel-level image fusion is recognized as having high significance in a …
Deep gradient projection networks for pan-sharpening
Pan-sharpening is an important technique for remote sensing imaging systems to obtain
high resolution multispectral images. Recently, deep learning has become the most popular …
high resolution multispectral images. Recently, deep learning has become the most popular …