CNN designed for pansharpening

Related tags

Deep LearningPBSNet
Overview

PROGRESSIVE BAND-SEPARATED CONVOLUTIONAL NEURAL NETWORK FOR MULTISPECTRAL PANSHARPENING

This repository contains main code for the paper PROGRESSIVE BAND-SEPARATED CONVOLUTIONAL NEURAL NETWORK FOR MULTISPECTRAL PANSHARPENING, contributed by Shishi Xiao, Cheng Jin, Tian-Jing Zhang, Ran Ran, and Liang-Jian Deng. All rights reserved by authors.

Homepage:

https://serendipitysx.github.io/

https://chengjin-git.github.io/

https://liangjiandeng.github.io/

Introduction

In this paper, we design a progressive, band-separated convolutional network architecture for discriminatively learning the features and relation among spectral bands, aiming to address the problem mentioned before. More specififically, the proposed architecture mainly consists of three aspects. First, to accurately preserve the spectral peculiarities, we divide the multispectral input image in terms of its bands into several groups. Second, our original panchromatic and multispectral inputs are fifiltered by a high-pass operation to further yield more spatial details. Third, we use a spectral fusion module (SFM) for each group and associate them to progressively assemble the whole architecture. It is worth mentioning that the architecture could be integrated into any other competitive CNNs to improve the performance.

Dependencies and Installation

  • Python 3.8 (Recommend to use Anaconda)
  • PyTorch > 1.1
  • NVIDIA GPU + CUDA
  • Python packages: pip install numpy scipy h5py
  • TensorBoard

Dataset Preparation

The datasets used in this paper is WorldView-3 (can be downloaded here), QuickBird (can be downloaded here) and GaoFen-2 (can be downloaded here). Due to the copyright of dataset, we can not upload the datasets, you may download the data and simulate them according to the paper.

PBSNet Architecture

Results

Citation

@INPROCEEDINGS{psbnnet,
  author={Xiao, Shi-Shi and Jin, Cheng and Zhang, Tian-Jing and Ran, Ran and Deng, Liang-Jian},
  booktitle={2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS}, 
  title={Progressive Band-Separated Convolutional Neural Network for Multispectral Pansharpening}, 
  year={2021},
  volume={},
  number={},
  pages={4464-4467},
  doi={10.1109/IGARSS47720.2021.9554024}}

Contact

We are glad to hear from you. If you have any questions, please feel free to contact or open issues on this repository.

Owner
SerendipitysX
SerendipitysX
MIM: MIM Installs OpenMMLab Packages

MIM provides a unified API for launching and installing OpenMMLab projects and their extensions, and managing the OpenMMLab model zoo.

OpenMMLab 254 Jan 04, 2023
Code for SALT: Stackelberg Adversarial Regularization, EMNLP 2021.

SALT: Stackelberg Adversarial Regularization Code for Adversarial Regularization as Stackelberg Game: An Unrolled Optimization Approach, EMNLP 2021. R

Simiao Zuo 10 Jan 10, 2022
[CVPR2021] Domain Consensus Clustering for Universal Domain Adaptation

[CVPR2021] Domain Consensus Clustering for Universal Domain Adaptation [Paper] Prerequisites To install requirements: pip install -r requirements.txt

Guangrui Li 84 Dec 26, 2022
TransMorph: Transformer for Medical Image Registration

TransMorph: Transformer for Medical Image Registration keywords: Vision Transformer, Swin Transformer, convolutional neural networks, image registrati

Junyu Chen 180 Jan 07, 2023
Code for EmBERT, a transformer model for embodied, language-guided visual task completion.

Code for EmBERT, a transformer model for embodied, language-guided visual task completion.

41 Jan 03, 2023
An interactive DNN Model deployed on web that predicts the chance of heart failure for a patient with an accuracy of 98%

Heart Failure Predictor About A Web UI deployed Dense Neural Network Model Made using Tensorflow that predicts whether the patient is healthy or has c

Adit Ahmedabadi 0 Jan 09, 2022
Codebase for Diffusion Models Beat GANS on Image Synthesis.

Codebase for Diffusion Models Beat GANS on Image Synthesis.

Katherine Crowson 128 Dec 02, 2022
Supervised domain-agnostic prediction framework for probabilistic modelling

A supervised domain-agnostic framework that allows for probabilistic modelling, namely the prediction of probability distributions for individual data

The Alan Turing Institute 112 Oct 23, 2022
Sync2Gen Code for ICCV 2021 paper: Scene Synthesis via Uncertainty-Driven Attribute Synchronization

Sync2Gen Code for ICCV 2021 paper: Scene Synthesis via Uncertainty-Driven Attribute Synchronization 0. Environment Environment: python 3.6 and cuda 10

Haitao Yang 62 Dec 30, 2022
SPEAR: Semi suPErvised dAta progRamming

Semi-Supervised Data Programming for Data Efficient Machine Learning SPEAR is a library for data programming with semi-supervision. The package implem

decile-team 91 Dec 06, 2022
Graph Transformer Architecture. Source code for

Graph Transformer Architecture Source code for the paper "A Generalization of Transformer Networks to Graphs" by Vijay Prakash Dwivedi and Xavier Bres

NTU Graph Deep Learning Lab 561 Jan 08, 2023
Next-gen Rowhammer fuzzer that uses non-uniform, frequency-based patterns.

Blacksmith Rowhammer Fuzzer This repository provides the code accompanying the paper Blacksmith: Scalable Rowhammering in the Frequency Domain that is

Computer Security Group @ ETH Zurich 173 Nov 16, 2022
xitorch: differentiable scientific computing library

xitorch is a PyTorch-based library of differentiable functions and functionals that can be widely used in scientific computing applications as well as deep learning.

24 Apr 15, 2021
Implementation of Hourglass Transformer, in Pytorch, from Google and OpenAI

Hourglass Transformer - Pytorch (wip) Implementation of Hourglass Transformer, in Pytorch. It will also contain some of my own ideas about how to make

Phil Wang 61 Dec 25, 2022
A static analysis library for computing graph representations of Python programs suitable for use with graph neural networks.

python_graphs This package is for computing graph representations of Python programs for machine learning applications. It includes the following modu

Google Research 258 Dec 29, 2022
nextPARS, a novel Illumina-based implementation of in-vitro parallel probing of RNA structures.

nextPARS, a novel Illumina-based implementation of in-vitro parallel probing of RNA structures. Here you will find the scripts necessary to produce th

Jesse Willis 0 Jan 20, 2022
ROMP: Monocular, One-stage, Regression of Multiple 3D People, ICCV21

Monocular, One-stage, Regression of Multiple 3D People ROMP, accepted by ICCV 2021, is a concise one-stage network for multi-person 3D mesh recovery f

Yu Sun 937 Jan 04, 2023
Toontown House CT Edition

Toontown House: Classic Toontown House Classic source that should just work. ❓ W

Open Source Toontown Servers 5 Jan 09, 2022
A library for efficient similarity search and clustering of dense vectors.

Faiss Faiss is a library for efficient similarity search and clustering of dense vectors. It contains algorithms that search in sets of vectors of any

Meta Research 18.8k Jan 08, 2023
An open software package to develop BCI based brain and cognitive computing technology for recognizing user's intention using deep learning

An open software package to develop BCI based brain and cognitive computing technology for recognizing user's intention using deep learning

deepbci 272 Jan 08, 2023