PSTLFusion

This is the official Tensorflow implementation of "Infrared and Visible Image Fusion via Parallel Scene and Texture Learning".

Overall Framework

The overall framework of the fusion process of proposed method.

Network Architecture

The architecture of the proposed infrared and visible image fusion method via parallel scene and texture learning.

To Train

Run python main.py --phase train to train your model. The format of the training data must be HDF5.

To Test

Run python main.py --phase guide to test the model.

Fusion Example

Qualitative comparison of PSTLFusion with 7 state-of-the-art methods on TNO and RoadScene datasets.

Detection Result

These are some object detection results for infrared, visible and fused images from the MFNet dataset. We pre-train the YOLOv5 detector on the CoCo dataset and deploy it on our fused result.

If this work is helpful to you, please cite it as:

@article{xu2022infrared,
  title={Infrared and visible image fusion via parallel scene and texture learning},
  author={Xu, Meilong and Tang, Linfeng and Zhang, Hao and Ma, Jiayi},
  journal={Pattern Recognition},
  pages={108929},
  year={2022},
  publisher={Elsevier}
}