Pansharpening
21 papers with code • 10 benchmarks • 4 datasets
As a remote sensing image processing task, Pan-sharpening aims to increase the spatial resolution of the low-resolution multispectral image with the guidance of the corresponding panchromatic image.
Benchmarks
These leaderboards are used to track progress in Pansharpening
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WorldView-3 PAirMax
PanCollection
Most implemented papers
Pansharpening by convolutional neural networks in the full resolution framework
matciotola/z-pnn
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A further problem is the scarcity of training data, which causes a limited generalization ability and a poor performance on off-training test images.
Content-Adaptive Non-Local Convolution for Remote Sensing Pansharpening
duanyll/canconv
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In this paper, we introduce a so-called content-adaptive non-local convolution (CANConv), a novel method tailored for remote sensing image pansharpening.
Pansharpening via Detail Injection Based Convolutional Neural Networks
XiaoXiao-Woo/PanCollection
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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 spatial resolution of the latter.
Rethinking CNN-Based Pansharpening: Guided Colorization of Panchromatic Images via GANs
Convolutional Neural Networks (CNN)-based approaches have shown promising results in pansharpening of satellite images in recent years.
Guided Deep Decoder: Unsupervised Image Pair Fusion
tuezato/guided-deep-decoder
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ECCV 2020
The proposed network is composed of an encoder-decoder network that exploits multi-scale features of a guidance image and a deep decoder network that generates an output image.
Learning deep multiresolution representations for pansharpening
sohaibali01/deep_pyramid_fusion
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Retaining spatial characteristics of panchromatic image and spectral information of multispectral bands is a critical issue in pansharpening.
Deep Convolutional Sparse Coding Network for Pansharpening with Guidance of Side Information
Pansharpening is a fundamental issue in remote sensing field.
Pansharpening PRISMA Data for Marine Plastic Litter Detection Using Plastic Indexes
The required pre-processing steps have been defined and 13 pansharpening methods have been applied and evaluated for their ability to spectrally discriminate plastics from water.
Sentinel-2 Sharpening Using a Single Unsupervised Convolutional Neural Network With MTF-Based Degradation Model
hvn2/S2S_UCNN
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2021
However, the downside of those methods is that the DL-based methods need to be trained separately for the 20 m and the 60 m bands in a supervised manner at reduced resolution, while the model-based methods heavily depend on the hand-crafted image priors.
Hyperspectral Pansharpening Based on Improved Deep Image Prior and Residual Reconstruction
To estimate the PAN image of the up-sampled HSI, we also propose a learnable spectral response function (SRF).
