Hyperspectral pansharpening: A review
L Loncan, LB De Almeida… - … and remote sensing …, 2015 - ieeexplore.ieee.org
Pansharpening aims at fusing a panchromatic image with a multispectral one, to generate
an image with the high spatial resolution of the former and the high spectral resolution of the …
an image with the high spatial resolution of the former and the high spectral resolution of the …
Domain adaptation for the classification of remote sensing data: An overview of recent advances
The success of the supervised classification of remotely sensed images acquired over large
geographical areas or at short time intervals strongly depends on the representativity of the …
geographical areas or at short time intervals strongly depends on the representativity of the …
Advanced multi-sensor optical remote sensing for urban land use and land cover classification: Outcome of the 2018 IEEE GRSS data fusion contest
This paper presents the scientific outcomes of the 2018 Data Fusion Contest organized by
the Image Analysis and Data Fusion Technical Committee of the IEEE Geoscience and …
the Image Analysis and Data Fusion Technical Committee of the IEEE Geoscience and …
MugNet: Deep learning for hyperspectral image classification using limited samples
In recent years, deep learning based methods have attracted broad attention in the field of
hyperspectral image classification. However, due to the massive parameters and the …
hyperspectral image classification. However, due to the massive parameters and the …
Data fusion and remote sensing: An ever-growing relationship
Characterized by a certain focus on the heavily discussed topic of image fusion in its
beginnings, sensor data fusion has played a significant role in the remote sensing research …
beginnings, sensor data fusion has played a significant role in the remote sensing research …
Pansharpening via detail injection based convolutional neural networks
Pansharpening aims to fuse a multispectral (MS) image with an associated panchromatic
(PAN) image, producing a composite image with the spectral resolution of the former and the …
(PAN) image, producing a composite image with the spectral resolution of the former and the …
Machine learning based hyperspectral image analysis: a survey
Hyperspectral sensors enable the study of the chemical properties of scene materials
remotely for the purpose of identification, detection, and chemical composition analysis of …
remotely for the purpose of identification, detection, and chemical composition analysis of …
Detail-injection-model-inspired deep fusion network for pansharpening
Pansharpening is an image fusion procedure, which aims to produce a high spatial
resolution multispectral (MS) image by combining a low spatial resolution MS image and a …
resolution multispectral (MS) image by combining a low spatial resolution MS image and a …
Hyperspectral pansharpening using deep prior and dual attention residual network
Convolutional neural networks (CNNs) have recently achieved impressive improvements on
hyperspectral (HS) pansharpening. However, most of the CNN-based HS pansharpening …
hyperspectral (HS) pansharpening. However, most of the CNN-based HS pansharpening …
Hyperspectral image super-resolution using deep convolutional neural network
Limited by the existed imagery hardware, it is challenging to obtain a hyperspectral image
(HSI) with a high spatial resolution. Super-resolution (SR) focuses on the ways to enhance …
(HSI) with a high spatial resolution. Super-resolution (SR) focuses on the ways to enhance …