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

matciotola/z-pnn 16 Nov 2021

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

matciotola/lambda-pnn 26 Jul 2023

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

Z-ypnos/SSDiff_main 17 Apr 2024

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

coder-qicao/zs-pan 9 Jul 2024

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

XiaoXiao-Woo/PanCollection 23 Jun 2018

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

ozcelikfu/PanColorGAN 30 Jun 2020

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 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 16 Feb 2021

Retaining spatial characteristics of panchromatic image and spectral information of multispectral bands is a critical issue in pansharpening.

Pansharpening PRISMA Data for Marine Plastic Litter Detection Using Plastic Indexes

vkristoll/Pansharpening-PRISMA-CNNs IEEE Access 2021

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.