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 …
A review of image fusion techniques for pan-sharpening of high-resolution satellite imagery
Pan-sharpening methods are commonly used to synthesize multispectral and panchromatic
images. Selecting an appropriate algorithm that maintains the spectral and spatial …
images. Selecting an appropriate algorithm that maintains the spectral and spatial …
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 …
PSGAN: A generative adversarial network for remote sensing image pan-sharpening
This article addresses the problem of remote sensing image pan-sharpening from the
perspective of generative adversarial learning. We propose a novel deep neural network …
perspective of generative adversarial learning. We propose a novel deep neural network …
Robust band-dependent spatial-detail approaches for panchromatic sharpening
G Vivone - IEEE transactions on Geoscience and Remote …, 2019 - ieeexplore.ieee.org
Pansharpening refers to the fusion of a multispectral (MS) image with a finer spectral
resolution but coarser spatial resolution than a panchromatic (PAN) image. The classical …
resolution but coarser spatial resolution than a panchromatic (PAN) image. The classical …
A benchmarking protocol for pansharpening: Dataset, preprocessing, and quality assessment
Comparative evaluation is a requirement for reproducible science and objective assessment
of new algorithms. Reproducible research in the field of pansharpening of very high …
of new algorithms. Reproducible research in the field of pansharpening of very high …
Laplacian pyramid networks: A new approach for multispectral pansharpening
Pansharpening is about fusing a high spatial resolution panchromatic image with a
simultaneously acquired multispectral image with lower spatial resolution. In this paper, we …
simultaneously acquired multispectral image with lower spatial resolution. In this paper, we …
Full scale regression-based injection coefficients for panchromatic sharpening
Pansharpening is usually related to the fusion of a high spatial resolution but low spectral
resolution (panchromatic) image with a high spectral resolution but low spatial resolution …
resolution (panchromatic) image with a high spectral resolution but low spatial resolution …