PolSARFormer: Local Window Attention Transformer for Polarimetric SAR Image Classification
February 11, 2024 ยท View on GitHub
Ali Jamali, Swalpa Kumar Roy, Avik Bhattacharya, and Pedram Ghamisi
This Keras code is for the paper A. Jamali, S. K. Roy, A. Bhattacharya and P. Ghamisi, "Local Window Attention Transformer for Polarimetric SAR Image Classification," in IEEE Geoscience and Remote Sensing Letters, doi: 10.1109/LGRS.2023.3239263 [https://ieeexplore.ieee.org/document/10024822].
Dataset
Flevoland dataset: NASA/JPL AIRSAR recorded the data of Flevoland, situated in the Netherlands, on August 16, 1989. The Flevoland image is $750\times1024$ pixels in size.
San Francisco dataset: The San Francisco illustrates a NASA/JPL AIRSAR L-band image of the San Francisco area. The resolution of the data of the San Francisco is $900\times1024$ pixels.
Appreciation from Geoscience and Remote Sensing Society (GRSS)
Citation
Please kindly cite the papers if this code is useful and helpful for your research.
@article{jamali2023local,
title={Local window attention transformer for polarimetric SAR image classification},
author={Jamali, Ali and Roy, Swalpa Kumar and Bhattacharya, Avik and Ghamisi, Pedram},
journal={IEEE Geoscience and Remote Sensing Letters},
volume={20},
pages={1--5},
year={2023},
publisher={IEEE}
}
Acknowledgement
Part of the local window attention (LWA) block is implementated from Neighborhood Attention Transformer.
License
Copyright (c) 2023 Ali Jamali. Released under the MIT License. See LICENSE for details.