/Pan-Mamba

Pan-Mamba: Effective Pan-Sharpening with State Space Model

Primary LanguagePython

Pan-Mamba: Effective Pan-Sharpening with State Space Model

Welcome to the official repository of Pan-Mamba, a powerful pan-sharpening algorithm leveraging the State Space Model. This repository provides the implementation of Pan-Mamba, along with resources for remote sensing researchers interested in pan-sharpening techniques.

Paper Reference

For a detailed understanding of the Pan-Mamba algorithm, please refer to the paper: Pan-Mamba: Effective Pan-Sharpening with State Space Model

Usage Guide

If you are a remote sensing user looking to enhance the quality of your images through pan-sharpening, you can find relevant information in the pan-sharpening folder. This section includes pre-trained checkpoints, inference code, and training code to help you apply Pan-Mamba to your remote sensing data.

For Module Integration

If you are interested in integrating our proposed block into your existing projects or workflows, the mamba block folder contains modules and blocks that can be easily incorporated.

Quick Start

  1. Clone the repository:
git clone https://github.com/alexhe101/Pan-Mamba.git
  1. Explore the pan-sharpening folder for remote sensing applications or the mamba block folder for module integration.

  2. Follow the guidelines provided in the respective folders to apply Pan-Mamba to your specific use case.

Issues and Contributions

Issues If you encounter any issues or have suggestions for improvement, please feel free to open an issue in the GitHub issue tracker.

Thank you for choosing Pan-Mamba for your pan-sharpening needs! We hope it proves to be a valuable tool in enhancing your remote sensing imagery.