Name
Abstract | ||
|---|---|---|
Multispectral satellite imaging sensors acquire various spectral band images and have a unique spectroscopic property in each band. Unfortunately, image artifacts from imaging sensor noise often affect the quality of scenes and have a negative impact on applications for satellite imagery. Recently, deep learning approaches have been extensively explored to remove noise in satellite imagery. Most d... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TGRS.2020.3025601 | IEEE Transactions on Geoscience and Remote Sensing |
Keywords | DocType | Volume |
Noise reduction,Satellites,Satellite broadcasting,Noise measurement,Sensors,Machine learning,Gallium nitride | Journal | 59 |
Issue | ISSN | Citations |
8 | 0196-2892 | 1 |
PageRank | References | Authors |
0.36 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Young-Joon Song | 1 | 2 | 1.74 |
| Jae-Heon Jeong | 2 | 1 | 0.36 |
| Dae-Soon Park | 3 | 1 | 0.36 |
| Hyun-Ho Kim | 4 | 1 | 0.36 |
| Doo-Chun Seo | 5 | 24 | 3.54 |
| Jong Chul Ye | 6 | 715 | 79.99 |