Quantitative evaluation metrics for image fusion.
源代码位于 '. /Evaluation' ;源图像请放在 './Image/Source-Image'目录下; 融合结果请放在'./Image/Algorithm'目录下。
1. 修改Evaluation_for_single_image.m 文件中源图像和融合结果的路径
2. 运行Evaluation_for_single_image.m
1. 修改Evaluation_for_single_algorithm.m 文件中源图像和融合结果的路径
2. 运行Evaluation_for_single_algorithm.m
1. 修改Evaluation_for_multi_algorithm.m 文件中源图像和融合结果的路径
2. 运行Evaluation_for_multi_algorithm.m
如果具有一定Matlab编程基础的用户可以直接尝试运行Evaluation_for_single_algorithm.m或者Evaluation_for_multi_algorithm.m来评估一个或多个算法的性能,如果对Matlab不熟练的话,请先从单幅图像评估开始。
对于图像融合领域的论文整理已开源至:https://github.com/Linfeng-Tang/Image-Fusion
如果我们的程序对你有所帮助请引用以下论文:
@inproceedings{Tang2024DRMF,
title={DRMF: Degradation-Robust Multi-Modal Image Fusion via Composable Diffusion Prior},
author={Tang, Linfeng and Deng, Yuxin and Yi, Xunpeng and Yan, Qinglong and Yuan, Yixuan and Ma, Jiayi},
booktitle=Proceedings of the ACM International Conference on Multimedia,
year={2024}
}
@article{Tang2022SeAFusion,
title = {Image fusion in the loop of high-level vision tasks: A semantic-aware real-time infrared and visible image fusion network},
author = {Linfeng Tang and Jiteng Yuan and Jiayi Ma},
journal = {Information Fusion},
volume = {82},
pages = {28-42},
year = {2022},
issn = {1566-2535},
publisher={Elsevier}
}
@article{Tang2022PIAFusion,
title={PIAFusion: A progressive infrared and visible image fusion network based on illumination aware},
author={Tang, Linfeng and Yuan, Jiteng and Zhang, Hao and Jiang, Xingyu and Ma, Jiayi},
journal={Information Fusion},
volume = {83-84},
pages = {79-92},
year = {2022},
issn = {1566-2535},
publisher={Elsevier}
}
@article{ma2021STDFusionNet,
title={STDFusionNet: An Infrared and Visible Image Fusion Network Based on Salient Target Detection},
author={Jiayi Ma, Linfeng Tang, Meilong Xu, Hao Zhang, and Guobao Xiao},
journal={IEEE Transactions on Instrumentation and Measurement},
year={2021},
volume={70},
number={},
pages={1-13},
doi={10.1109/TIM.2021.3075747},
publisher={IEEE}
}
如果有任何问题请联系:linfeng0419@gmail.com