This is the PyTorch implementation of paper "Remote sensing pan-sharpening based on channel fusion and progressive enhancement".
Before running the codes, you should modify the input path in codes according to your datasets. The related codes of this part are all in 'process_data' folder.
You can generate your datasets as follows:
cd process_data
python real_processing.py
python to_patch.py
You can just modify the args in args.py and run
python train.py
The logs and the model will be saved in the 'log' and 'checkpoint' folders respectively.
You can just modify the args in testsolver.py and run
python test.py
Generally the results will be generated below the 'output' folder.
Ubuntu 16.04.6 LTS
Python 3.7.0
main python packages:
gdal = 2.3.2
pytorch = 1.9.1
torchvision = 0.10.1
opencv-python = 4.5.3.56
cudatoolkit = 11.1.74
@article{jia2023channel,
author = {贾雅男 and 郭晓杰},
title = {通道融合的渐进增强遥感图像全色锐化算法},
journal = {中国图象图形学报},
year = {2023},
volume = {28},
number = {01},
pages = {305--316},
}
@article{jia2023channel,
author = {Yanan Jia and Xiaojie Guo},
title = {Remote sensing pan-sharpening based on channel fusion and progressive enhancement},
journal = {Journal of image and Graphics},
year = {2023},
volume = {28},
number = {01},
pages = {305--316},
}