{"id":28075149,"url":"https://github.com/liuuuuu777/imagefusion-evaluation","last_synced_at":"2026-03-07T01:35:21.776Z","repository":{"id":252801017,"uuid":"841381999","full_name":"liuuuuu777/ImageFusion-Evaluation","owner":"liuuuuu777","description":"This is the repo for Image Fusion evaluation, containing metric EN, CE, MI, FMI_pixel, FMI_dct, FMI_w, PSNR, MSSSIM, RMSE, SF, SD, Variance, EI, AG, VIF, Qcb, Qabf, CC, SCD, Nabf, Qcv.","archived":false,"fork":false,"pushed_at":"2024-08-13T08:27:43.000Z","size":181,"stargazers_count":6,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-05-13T00:06:04.077Z","etag":null,"topics":["evaluation-functions","matlab"],"latest_commit_sha":null,"homepage":"","language":"MATLAB","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/liuuuuu777.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-08-12T09:46:10.000Z","updated_at":"2025-04-13T13:17:32.000Z","dependencies_parsed_at":"2024-10-24T13:09:29.407Z","dependency_job_id":"e4caf90e-c622-4775-8a19-8ac9f652f980","html_url":"https://github.com/liuuuuu777/ImageFusion-Evaluation","commit_stats":null,"previous_names":["l1uuuuu/imagefusion-for-ivif-evaluation","bfliu7/imagefusion-evaluation","liuuuuu777/imagefusion-evaluation"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/liuuuuu777%2FImageFusion-Evaluation","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/liuuuuu777%2FImageFusion-Evaluation/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/liuuuuu777%2FImageFusion-Evaluation/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/liuuuuu777%2FImageFusion-Evaluation/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/liuuuuu777","download_url":"https://codeload.github.com/liuuuuu777/ImageFusion-Evaluation/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":253843215,"owners_count":21972873,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["evaluation-functions","matlab"],"created_at":"2025-05-13T00:06:13.138Z","updated_at":"2026-03-07T01:35:21.734Z","avatar_url":"https://github.com/liuuuuu777.png","language":"MATLAB","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Image Fusion Evaluation\n\n\n## 📰 News\n* [2024-08-12] **Open-sourcing evaluation code with 21 metrics for infrared and visible image fusion!** \n\n## 🗼 Platform\n* Matlab\n\n## 🚩 Structure of Folder\n```\nDataset Folder\n    ├─21_pairs_tno\n    │  ├─ccfuse\n    │  │    Fuse1.png\n    │  │    Fuse10.png\n    │  │    ......\n    │  │\n    │  ├─ir\n    │  │    IR1.png\n    │  │    IR10.png\n    │  │    ......\n    │  │\n    │  └─vis\n    │       VIS1.png\n    │       VIS10.png\n    │       ......     \n    │\n    ├─40_vot_tno\n    │  ├─ir\n    │  │    IR1.png\n    │  │    IR11.png\n    │  │    ......\n    │  │\n    │  └─vis\n    │       VIS1.png\n    │       VIS11.png\n    │       ......\n    │       \n    └─output\n        └─21_pairs_tno\n            └─ccfuse\n                ├─evaluation_metrics\n                │      all_results.txt\n                │\n                └─evaluation_metrics_single\n                        Fuse1.txt\n                        Fuse10.txt\n                        ......\n                        output_single.xlsx\n```\n* As shown above, **21_pairs_tno** and **40_vot_tno** are the folders of the dataset, and **output** is the result after running evaluation.\n* Take the dataset **21_pairs_tno** as an example. Folder **ir** holds the infrared images, referring to **the format of \"IR1.png\"**. Folder **vis** holds the infrared images, referring to the format of **\"VIS1.png\"**. Folder **ccfuse** holds the fused results, which name of refers to **\"Fuse1.png\"**. \n* **\".png\"**, **\".jpg\"** and **'.bmp'** are all allowed to use.\n* Folder output classifies the data first by dataset and then by algorithm. **Evaluation_metrics** holds the average of all fused images, and **evaluation_metrics_single** holds fused images separately.\n\n\n## 💁 Get Started\n* Git clone the repository.\n* Prepare the data as the structure of folder.\n* Get to the project of top folder. \n* Change the default path in amain.m\n```\nvifb_path = \"datasetexample\\\"; % better to use an absolute path\nbench = \"21_pairs_tno\";\nmethod = \"ccfuse\";\n```\n    \n## 🖼️ Metrics\n* Entropy(EN)\n* Cross Entropy(CE)\n* Mutual Information(MI)\n* FMI_pixel\n* FMI_dct\n* FMI_w\n* Peak signal to noise ratio(PSNR)\n* MS structural similarity(MS-SSIM)\n* Root mean square error(RMSE)\n* Spaial Frequency(SF)\n* Standard deviation(SD)\n* Variance\n* Edge Intensity(EI)\n* Average gradient(AG)\n* VIF\n* Qcb\n* Gradient based similarity measurement(Qabf)\n* Correlation coefficient(CC)\n* Sum of correlation differences(SCD)\n* Nabf\n* Qcv\n\n\n\n\n\n\n## 📈 Star Rising\n\u003cpicture\u003e\n  \u003csource\n    media=\"(prefers-color-scheme: dark)\"[README (1).md](README%20%281%29.md)\n    srcset=\"\n      https://api.star-history.com/svg?repos=bfliu7/ImageFusion-Evaluation\u0026type=Date\u0026theme=dark\n    \"\n  /\u003e\n  \u003csource\n    media=\"(prefers-color-scheme: light)\"\n    srcset=\"\n      https://api.star-history.com/svg?repos=bfliu7/ImageFusion-Evaluation\u0026type=Date\n    \"\n  /\u003e\n  \u003cimg\n    alt=\"Star History Chart\"\n    src=\"https://api.star-history.com/svg?repos=bfliu7/ImageFusion-Evaluation\u0026type=Date\"\n  /\u003e\n\u003c/picture\u003e\n\n\n\n## 📋 Citation\nThanks to [Linfeng Tang](https://github.com/Linfeng-Tang/Image-Fusion/tree/main) and [Chenzhang Xing](https://github.com/xingchenzhang/VIFB) for the open source code, please cite these papers if you are using this code.\n\n```bibtex\n@article{Tang2022Survey,\n  title={Deep learning-based image fusion: A survey},\n  author={Tang, Linfeng and Zhang, Hao and Xu, Han and Ma, Jiayi},  \n  journal={Journal of Image and Graphics}\n  volume={28},\n  number={1},\n  pages={3--36},\n  year={2023}\n}\n\n\n@article{Tang2022SuperFusion,\n  title={SuperFusion: A versatile image registration and fusion network with semantic awareness},\n  author={Tang, Linfeng and Deng, Yuxin and Ma, Yong and Huang, Jun and Ma, Jiayi},\n  journal={IEEE/CAA Journal of Automatica Sinica},\n  volume={9},\n  number={12},\n  pages={2121--2137},\n  year={2022},\n  publisher={IEEE}\n}\n\n\n@article{Ma2022SwinFusion,\n  title={SwinFusion: Cross-domain Long-range Learning for General Image Fusion via Swin Transformer},\n  author={Ma, Jiayi and Tang, Linfeng and Fan, Fan and Huang, Jun and Mei, Xiaoguang and Ma, Yong},\n  journal={IEEE/CAA Journal of Automatica Sinica},\n  volume={9},\n  number={7},\n  pages={1200--1217},\n  year={2022},\n  publisher={IEEE}\n}\n\n\n@article{TangSeAFusion,\ntitle = {Image fusion in the loop of high-level vision tasks: A semantic-aware real-time infrared and visible image fusion network},\nauthor = {Linfeng Tang and Jiteng Yuan and Jiayi Ma},\njournal = {Information Fusion},\nvolume = {82},\npages = {28-42},\nyear = {2022},\nissn = {1566-2535},\npublisher={Elsevier}\n}\n\n\n@article{Tang2022DIVFusion,\n  title={DIVFusion: Darkness-free infrared and visible image fusion},\n  author={Tang, Linfeng and Xiang, Xinyu and Zhang, Hao and Gong, Meiqi and Ma, Jiayi},\n  journal={Information Fusion},\n  volume = {91},\n  pages = {477-493},\n  year = {2023},\n  publisher={Elsevier}\n}\n\n\n@article{Tang2022PIAFusion,\n  title={PIAFusion: A progressive infrared and visible image fusion network based on illumination aware},\n  author={Tang, Linfeng and Yuan, Jiteng and Zhang, Hao and Jiang, Xingyu and Ma, Jiayi},\n  journal={Information Fusion},\n  volume = {83-84},\n  pages = {79-92},\n  year = {2022},\n  issn = {1566-2535},\n  publisher={Elsevier}\n}\n\n\n@article{Ma2021STDFusionNet,\n  title={STDFusionNet: An Infrared and Visible Image Fusion Network Based on Salient Target Detection},\n  author={Jiayi Ma, Linfeng Tang, Meilong Xu, Hao Zhang, and Guobao Xiao},\n  journal={IEEE Transactions on Instrumentation and Measurement},\n  year={2021},\n  volume={70},\n  number={},\n  pages={1-13},\n  doi={10.1109/TIM.2021.3075747}，\n  publisher={IEEE}\n}\n\n\n\n@inproceedings{zhang2020vifb,\ntitle={VIFB: A Visible and Infrared Image Fusion Benchmark},\nauthor={Zhang, Xingchen and Ye, Ping and Xiao, Gang},\nbooktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},\nyear={2020}}  \n\n\n@article{zhang2023visible,\ntitle={Visible and Infrared Image Fusion Using Deep Learning},\nauthor={Zhang, Xingchen and Demiris, Yiannis},\njournal={IEEE Transactions on Pattern Analysis and Machine Intelligence},\nyear={2023},\npublisher={IEEE}}\n```\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fliuuuuu777%2Fimagefusion-evaluation","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fliuuuuu777%2Fimagefusion-evaluation","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fliuuuuu777%2Fimagefusion-evaluation/lists"}