This example implements the paper in review [Fractional Gabor Convolutional Network for Multi-source Remote Sensing Data Classification]

A Fractional Gabor Convolutional Network for Multi-source Remote Sensing Data Classification. Evaluated on the dataset of Houston, Trento and MUUFL.

1. Houston dataset were introduced for the 2013 IEEE GRSS Data Fusion contest. Data set links comes from http://www.grss-ieee.org/community/technical-committees/data-fusion/2013-ieee-grss-data-fusion-contest/

2. The authors would like to thank Dr. P. Ghamisi for providing the Trento Data.

3. The MUUFL Gulfport Hyperspectral and LIDAR Data [1][2] is Available from https://github.com/GatorSense/MUUFLGulfport/.

[1] P. Gader, A. Zare, R. Close, J. Aitken, G. Tuell, “MUUFL Gulfport Hyperspectral and LiDAR Airborne Data Set,” University of Florida, Gainesville, FL, Tech. Rep. REP-2013-570, Oct. 2013.

[2] X. Du and A. Zare, “Technical Report: Scene Label Ground Truth Map for MUUFL Gulfport Data Set,” University of Florida, Gainesville, FL, Tech. Rep. 20170417, Apr. 2017. Available: http://ufdc.ufl.edu/IR00009711/00001.

Please modify line 48-59 in demoMUUFL.py for the dataset details.

Train the HSI and LiDAR-based DSM

python demo.py 

All the results are cited from original paper. More details can be found in the paper.

Please kindly cite the papers if this code is useful and helpful for your research.

X. Zhao, R. Tao, W. Li, W. Philips and W. Liao, "Fractional Gabor Convolutional Network for Multisource Remote Sensing Data Classification," in IEEE Transactions on Geoscience and Remote Sensing, doi: 10.1109/TGRS.2021.3065507.

@ARTICLE{9383794,  
  author={Zhao, Xudong and Tao, Ran and Li, Wei and Philips, Wilfried and Liao, Wenzhi},  
  journal={IEEE Transactions on Geoscience and Remote Sensing},   
  title={Fractional Gabor Convolutional Network for Multisource Remote Sensing Data Classification},   
  year={2021},  volume={},  number={},  pages={1-18},  
  doi={10.1109/TGRS.2021.3065507}
  }