Name
Abstract | ||
|---|---|---|
Due to the different imaging methods of SAR image and optical image, it is difficult to establish the corresponding relationship between them by traditional methods. However, with the development of deep learning, there are many researches on the transformation from SAR image to optical image based on GAN, which prove that the mapping between SAR image and optical image can be achieved. Based on this, this work will transform the SAR image into optical image and fuse to fill the cloud area of the optical image. This work will provide a method of heterogeneous image fusion to remove cloud, and get a good effect. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/Multi-Temp.2019.8866939 | 2019 10th International Workshop on the Analysis of Multitemporal Remote Sensing Images (MultiTemp) |
Keywords | Field | DocType |
Deep Learning,GAN,Cloud removal | Gallium nitride,Computer vision,Optical image,Image fusion,Computer science,Fusion,Artificial intelligence,Deep learning,Fuse (electrical),Adaptive optics,Cloud computing | Conference |
ISBN | Citations | PageRank |
978-1-7281-4616-4 | 0 | 0.34 |
References | Authors | |
1 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jianhao Gao | 1 | 3 | 2.78 |
| Hai Zhang | 2 | 0 | 0.68 |
| Qiangqiang Yuan | 3 | 583 | 41.52 |