Name
Abstract | ||
|---|---|---|
•We propose a new IR/VIS fusion method based on Generative Adversarial Networks.•It can keep both the thermal radiation and the texture details in the source images.•It is an end-to-end model and does not need to design fusion rules manually.•Our results look like sharpened IR images with highlighted target and abundant textures.•We generalize it to fuse images with different resolutions like thermal pan-sharpening. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.inffus.2018.09.004 | Information Fusion |
Keywords | Field | DocType |
Image fusion,Infrared image,Visible image,Generative adversarial network,Deep learning | Discriminator,Pattern recognition,Image fusion,Human visual system model,Fusion rules,Artificial intelligence,Fuse (electrical),Infrared,Upsampling,Image resolution,Mathematics | Journal |
Volume | ISSN | Citations |
48 | 1566-2535 | 49 |
PageRank | References | Authors |
1.07 | 17 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jiayi Ma | 1 | 1302 | 65.86 |
| wei yu | 2 | 62 | 8.23 |
| Pengwei Liang | 3 | 90 | 2.96 |
| chang li | 4 | 282 | 19.50 |
| Junjun Jiang | 5 | 1138 | 74.49 |