一、論文中常用的網址：
http://www.imagefusion.org （論文中經常引用，但是目前打不開）
二、多聚焦圖像：
1、http://www.pxleyes.com/photography-contest/19726
2、Lytro Multi-focus Dataset（常用，彩色多聚焦圖像）
“ This dataset contains 20 pairs of color multi-focus images of size 520×520 pixels and four series of multi-focus images with three sources.
Please cite the following paper if you use this dataset:
M. Nejati, S. Samavi, and S. Shirani, "Multi-focus Image Fusion Using Dictionary-Based Sparse Representation", Information Fusion, vol. 25, Sept. 2015, pp. 72-84.
網址：https://mansournejati.ece.iut.ac.ir/content/lytro-multi-focus-dataset
3、Paper：Slavica Savic, "Multifocus Image Fusion Based on Empirical Mode Decomposition", Twentieth International Electrotechnical and Computer Science Conference, ERK 2011.
網站內提供27對多聚焦圖像。
4、“The dataset which includes 150 different images is created to use in Multi-focus Image Fusion algorithms. This dataset is different from other datasets in this area. The new dataset includes more than two images to fuse. And this propoerty is very important for this dataset.The dataset is prepared by Samet Aymaz.”（包含150張圖像，21.3M）
https://github.com/sametaymaz/Multi-focus-Image-Fusion-Dataset
該網頁也提供了一些多聚焦圖像素材。
三、紅外與可見光圖像
1、Toet A. TNO Image fusion dataset. (117.03 MB)——圖像序列
網址：https://figshare.com/articles/TN_Image_Fusion_Dataset/1008029
（內容很豐富，常用的圖像都是從該庫裏挑出來的。論文中也常引用該網址。）
簡介：
"The TNO Image Fusion Dataset contains multispectral (intensified visual, near-infrared, and longwave infrared or thermal) nighttime imagery of different military relevant scenerios, registered with different multiband camnera systems."
2、OTCBVS Benchmark Dataset Collection
網址：http://vcipl-okstate.org/pbvs/bench/
網站內的簡介：
" This is a publicly available benchmark dataset for testing and evaluating novel and state-of-the-art computer vision algorithms. Several researchers and students have requested a benchmark of non-visible (e.g., infrared) images and videos. The benchmark contains videos and images recorded in and beyond the visible spectrum and is available for free to all researchers in the international computer vision communities. Also it will allow a large spectrum of IEEE and SPIE vision conference and workshop participants to explore the benefits of the non-visible spectrum in real-world applications, contribute to the OTCBVS workshop series, and boost this research field significantly. This effort was initiated by Dr. Riad I. Hammoud in 2004. It was hosted at Ohio State University and managed by Dr. James W. David until 2013. It is currently managed by Dr. Guoliang Fan at Oklahoma State University.
This benchmark is to be used for educational and research purposes only, and this benchmark must be acknowledged by the users.
其中通常使用第三個數據集——Dataset 03: OSU Color-Thermal Database
引用：IEEE OTCBVS WS Series Bench; J. Davis and V. Sharma, "Background-Subtraction using Contour-based Fusion of Thermal and Visible Imagery," Computer Vision and Image Understanding, Vol 106, No. 2-3, 2007, pp. 162-182.
3、DATA SET 3: Bristol Eden Project Multi-Sensor Data Set
http://www.cis.rit.edu/pelz/scanpaths/data/bristol-eden.htm
4、Visible-Infrared Database
http://www02.smt.ufrj.br/~fusion/
6、RGB-NIR Scene Dataset（大約1GB）（EPFL 2015 EPFL database）
網址：https://ivrl.epfl.ch/research-2/research-downloads/supplementary_material-cvpr11-index-html/
網站內的簡介：
“This dataset consists of 477 images in 9 categories captured in RGB and Near-infrared (NIR). The images were captured using separate exposures from modified SLR cameras, using visible and NIR filters. For more info on NIR photography, see the references below. The scene categories are: country, field, forest, indoor, mountain, oldbuilding, street, urban, water.”
四、醫學圖像：
www.med.harvard.edu/aanlib/home.html
五、真彩色圖像
最後：
Durga Prasad Bavirisetti提供了各種融合圖像數據集（下面的網址），包含醫學圖像，多聚焦圖像，多模態圖像，多曝光圖像，遙感圖像。（該庫裏的圖像與前面的鏈接裏的圖像會有重複）
網站：https://sites.google.com/view/durgaprasadbavirisetti/datasets