Coupled Tensor Decomposition for Hyperspectral Pansharpening
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Access"
DOI: 10.1109/access.2018.2850340
Abstract: This paper aims to effectively preserve the spatial and spectral information of hyperspectral (HS) images. For this purpose, the author proposed a new image fusion method based on coupled tensor decomposition (CTD). First, the wanted… read more here.
Keywords: tensor decomposition; hyperspectral pansharpening; tensor; coupled tensor ... See more keywords
An Improved Hyperspectral Pansharpening Algorithm Based on Optimized Injection Model
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2895550
Abstract: The hyperspectral pansharpening is a significant preprocessing technology in hyperspectral images application. A new optimized injection model-based hyperspectral pansharpening algorithm is proposed in this paper. Compared with the traditional pansharpening methods, the algorithm achieves two… read more here.
Keywords: hyperspectral pansharpening; pansharpening algorithm; injection model; optimized injection ... See more keywords
A Model-Inspired Approach With Transformers for Hyperspectral Pansharpening
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2022.3199207
Abstract: Hyperspectral pansharpening is a method of integrating a low-resolution hyperspectral image with a high-resolution panchromatic image to produce a high-resolution hyperspectral image. In recent years, a number of hyperspectral pansharpening methods have been developed by… read more here.
Keywords: hyperspectral pansharpening; transformers hyperspectral; inspired approach; model inspired ... See more keywords
A Deep-Shallow Fusion Network With Multidetail Extractor and Spectral Attention for Hyperspectral Pansharpening
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2022.3202866
Abstract: Hyperspectral (HS) pansharpening aims at fusing a low-resolution HS image with a high-resolution panchromatic (PAN) image to obtain a HS image with both higher spectral and spatial resolutions. However, existing HS pansharpening algorithms are mainly… read more here.
Keywords: shallow fusion; network; hyperspectral pansharpening; deep shallow ... See more keywords
Deep Residual Learning for Boosting the Accuracy of Hyperspectral Pansharpening
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2019.2945424
Abstract: Recently, deep learning (DL) has gained impressive achievements in the field of remote sensing image fusion. However, most of the previous DL-based fusion methods are originally designed for multispectral pansharpening, which cannot be readily employed… read more here.
Keywords: accuracy hyperspectral; learning boosting; deep residual; hyperspectral pansharpening ... See more keywords
Laplacian Pyramid Dense Network for Hyperspectral Pansharpening
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2021.3076768
Abstract: Hyperspectral (HS) pansharpening aims to create a pansharpened image that integrates the spatial details of the panchromatic (PAN) image and the spectral content of the HS image. In this article, we present a deep convolutional… read more here.
Keywords: network; laplacian pyramid; hyperspectral pansharpening; pyramid dense ... See more keywords
Multiobjective Guided Divide-and-Conquer Network for Hyperspectral Pansharpening
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2022.3159999
Abstract: Deep learning methods have gained rapid development in hyperspectral pansharpening (HP) due to powerful spatial–spectral feature extraction ability. However, most of these methods are optimized using a single reconstruction objective. It is difficult for these… read more here.
Keywords: divide conquer; network; spatial spectral; hyperspectral pansharpening ... See more keywords
Dynamic Hyperspectral Pansharpening CNNs
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2023.3250621
Abstract: Hyperspectral (HS) pansharpening seeks to integrate low spatial resolution HS (LRHS) images with connected panchromatic (PAN) images to produce high spatial resolution HS (HRHS) images. Traditional pansharpening convolutional neural networks (CNNs) directly map LRHS and… read more here.
Keywords: pansharpening cnns; hyperspectral pansharpening; dypnn; pansharpening rules ... See more keywords
Hyperspectral Pansharpening With Deep Priors
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Neural Networks and Learning Systems"
DOI: 10.1109/tnnls.2019.2920857
Abstract: Hyperspectral (HS) image can describe subtle differences in the spectral signatures of materials, but it has low spatial resolution limited by the existing technical and budget constraints. In this paper, we propose a promising HS… read more here.
Keywords: resolution; deep priors; high frequency; pansharpening deep ... See more keywords
Multi-level spatial details cross-extraction and injection network for hyperspectral pansharpening.
Sign Up to like & getrecommendations! Published in 2022 at "Optics letters"
DOI: 10.1364/ol.447405
Abstract: Hyperspectral (HS) pansharpening, which fuses the HS image with a high spatial resolution panchromatic (PAN) image, provides a good solution to overcome the limitation of HS imaging devices. However, most existing convolutional neural network (CNN)-based… read more here.
Keywords: injection; network; hyperspectral pansharpening; extraction ... See more keywords