Pansharpening by Combining Enhanced Spatial-Spectral Fidelity and Gradient-Domain Guided Filtering
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 Pansharpening techniques fuse the complementary information from a high-resolution panchromatic (PAN) and low-resolution multispectral (LRMS) images to produce a high-resolution multispectral (HRMS) image.
Li Liu +3 more
doaj +1 more source
Hyperspectral Super-Resolution with Coupled Tucker Approximation: Recoverability and SVD-based algorithms [PDF]
, 2019 We propose a novel approach for hyperspectral super-resolution, that is based on low-rank tensor approximation for a coupled low-rank multilinear (Tucker) model. We show that the correct recovery holds for a wide range of multilinear ranks.
Brie, David +3 more
core +2 more sources
Hyperspectral Pansharpening: Critical review, tools, and future perspectives [PDF]
IEEE Geoscience and Remote Sensing MagazineHyperspectral (HS) pansharpening consists of fusing a high-resolution panchromatic (PAN) band and a low-resolution HS image to obtain a new image with high resolution in both the spatial and spectral domains.
Matteo Ciotola +6 more
semanticscholar +1 more source
Computationally Inexpensive Landsat 8 Operational Land Imager (OLI) Pansharpening
Remote Sensing, 2016 Pansharpening algorithms fuse higher spatial resolution panchromatic with lower spatial resolution multispectral imagery to create higher spatial resolution multispectral images.
Hankui K. Zhang, David P. Roy
doaj +1 more source
A Swin Transformer with Dynamic High-Pass Preservation for Remote Sensing Image Pansharpening
Remote Sensing, 2023 Pansharpening is a technique used in remote sensing to combine high-resolution panchromatic (PAN) images with lower resolution multispectral (MS) images to generate high-resolution multispectral images while preserving spectral characteristics. Recently,
Weisheng Li +3 more
doaj +1 more source
Challenges and Opportunities of Multimodality and Data Fusion in Remote Sensing [PDF]
, 2015 International audience—Remote sensing is one of the most common ways to extract relevant information about the Earth and our environment. Remote sensing acquisitions can be done by both active (synthetic aperture radar, LiDAR) and passive (optical and ...
Benediktsson, Jon Atli +5 more
core +2 more sources
Pansharpening Using Guided Filtering to Improve the Spatial Clarity of VHR Satellite Imagery
Remote Sensing, 2019 Pansharpening algorithms are designed to enhance the spatial resolution of multispectral images using panchromatic images with high spatial resolutions. Panchromatic and multispectral images acquired from very high resolution (VHR) satellite sensors used
Jaewan Choi, Honglyun Park, Doochun Seo
doaj +1 more source
A Local and Nonlocal Feature Interaction Network for Pansharpening
Remote Sensing, 2022 Pansharpening based on deep learning (DL) has shown great advantages. Most convolutional neural network (CNN)-based methods focus on obtaining local features from multispectral (MS) and panchromatic (PAN) images, but ignore the nonlocal dependence on ...
Junru Yin +4 more
doaj +1 more source
IEEE Access, 2020 Pansharpening is a technique that fuses the coarser resolution of multispectral imagery (MS) with high spatial resolution panchromatic (PAN) imagery. Pansharpening is prone to spectral distortions based on the nature of the panchromatic band.
G. Rohith, Lakshmi Sutha Kumar
doaj +1 more source
Fast Fusion of Multi-Band Images Based on Solving a Sylvester Equation [PDF]
, 2015 International audienceThis paper proposes a fast multi-band image fusion algorithm, which combines a high-spatial low-spectral resolution image and a low-spatial high-spectral resolution image.
Dobigeon, Nicolas +2 more
core +4 more sources