https://github.com/andrewekhalel/mtl_pan_seg

Implementation of "Multi-task Deep Learning for Satellite Image Pansharpening and Segmentation"
https://github.com/andrewekhalel/mtl_pan_seg

multi-task-learning pansharpening satellite-imagery segmentation tensorflow

Last synced: 30 days ago
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Implementation of "Multi-task Deep Learning for Satellite Image Pansharpening and Segmentation"

• Host: GitHub
• URL: https://github.com/andrewekhalel/mtl_pan_seg
• Owner: andrewekhalel
• License: other
• Created: 2018-12-18T12:34:42.000Z (almost 6 years ago)
• Default Branch: master
• Last Pushed: 2018-12-18T13:20:27.000Z (almost 6 years ago)
• Last Synced: 2024-08-04T03:11:39.990Z (3 months ago)
• Topics: multi-task-learning, pansharpening, satellite-imagery, segmentation, tensorflow
• Language: Python
• Size: 55.2 MB
• Stars: 21
• Watchers: 3
• Forks: 10
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: license.txt

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README

        
## Implementation of the methods described in the paper entitled “Multi-task deep learning for satellite image pansharpening and segmentation”

### Multi-task Framework Architecture

![Framework](https://raw.githubusercontent.com/andrewekhalel/MTL_PAN_SEG/master/docs/figures/framework.png)

### Software Architecture

![Software Architecture](https://raw.githubusercontent.com/andrewekhalel/MTL_PAN_SEG/master/docs/figures/software_architecture.png)

### Dependencies

 - Python 3.6.4

 - Tensorflow 1.10.0

 - Numpy 1.14.2

 - GDAL 2.2.4  

The codes have been tested on Fedora 25

#### Visualization (Optional)

We recommend to use [QGIS](https://qgis.org/en/site/), where the outputs can easily be displayed despite of the image size.

### Usage

 - The solver sub-directories, namely training_solvers and test_solvers contain solvers, which train a model and test the trained model (See the figure under Software Architecture section).

 - To train a model, enter the following command (we assume that you are under multi-task directory, otherwise you will get an error): `python3 train_solvers/train_solver.py`

 - To test a trained model, enter this command: `python3 test_solvers/test_solver.py`  

  

`` in the commands above determines which solver to run.

### Example Visual Results From the World-View3 Dataset

Here, we illustrate several original visual outputs from the World-View3 dataset for different methods including our multi-task framework.

![Results](https://raw.githubusercontent.com/andrewekhalel/MTL_PAN_SEG/master/docs/figures/results.png)

### Citation

```

@inproceedings{khalel2019multi,

  title={Multi-task deep learning for satellite image pansharpening and segmentation},

  author={Khalel, Andrew and Tasar, Onur and Charpiat, Guillaume and Tarabalka, Yuliya},

  booktitle={IEEE International Geoscience and Remote Sensing Symposium--IGARSS 2019},

  year={2019}

}

```