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Fast and Efficient Zero-Learning Image Fusion

This repository provides an opencv and pytorch implementation of the paper "Fast and Efficient Zero-Learning Image Fusion".

Usage

pip install -r requirements.txt
cd code/
# --imageSource specify a sequence of source images to be fused
python main.py --imagePath=../images/IV_images --imageSource "VIS*.png" "IR*.png"
python main.py --imagePath=../images/MRI-PET --imageSource "MRI*.png" "PET*.png"

In the above example, VIS01.png will be fused with IR01.png, VIS02.png will be fused with IR02.png, etc.

Fusion of 1 RGB with multiple IR images are supported, just add the glob pattern of images in --imageSource.

Results

Visible and infrared Image fusion

Something went wrong, see Demo.ipynb for results demo

Grayscale and RGB image fusion

Something went wrong, please refer to Demo.ipynb or main.py

License

This project is licensed under the MIT License.

MIT © bsun

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An OpenCV and Pytorch implementation of Zero-Learning-Fast-Medical-Image-Fusion

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