Pansharpening
29 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.
Most implemented papers
Pansharpening by convolutional neural networks in the full resolution framework
A further problem is the scarcity of training data, which causes a limited generalization ability and a poor performance on off-training test images.
Unsupervised Deep Learning-based Pansharpening with Jointly-Enhanced Spectral and Spatial Fidelity
In latest years, deep learning has gained a leading role in the pansharpening of multiresolution images.
SSDiff: Spatial-spectral Integrated Diffusion Model for Remote Sensing Pansharpening
Pansharpening is a significant image fusion technique that merges the spatial content and spectral characteristics of remote sensing images to generate high-resolution multispectral images.
Variational Zero-shot Multispectral Pansharpening
The most challenging issue for this task is that only the to-be-fused LRMS and PAN are available, and the existing deep learning-based methods are unsuitable since they rely on many training pairs.
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 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
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
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.