Name
Title | ||
|---|---|---|
Infrared and Visible Image Fusion Using Dual Discriminators Generative Adversarial Networks with Wasserstein Distance |
Abstract | ||
|---|---|---|
•We employ Generative Multi-Adversarial networks to fuse source images.•We design two discriminators to preserve more intensity and texture information.•We propose LBP loss function to keep rich texture information from visible image.•Our method uses the WGAN to improve the performance of fusion method. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.ins.2020.04.035 | Information Sciences |
Keywords | DocType | Volume |
Wasserstein generative adversarial network,Image fusion,Local binary pattern,Infrared image,Visible image | Journal | 529 |
ISSN | Citations | PageRank |
0020-0255 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jing Li | 1 | 345 | 53.26 |
| Hongtao Huo | 2 | 3 | 1.05 |
| Kejian Liu | 3 | 0 | 0.34 |
| chang li | 4 | 282 | 19.50 |