Name
Abstract | ||
|---|---|---|
Super-resolution mapping (SRM) is a method to estimate a fine-resolution land cover map from coarse-resolution fraction images. SRM is an ill-posed problem and regularization terms are always needed to be introduced to well-pose the solution. The regularization term based on the maximal spatial dependence has been widely used in SRM; however, it is often too simple to provide detailed land cover p... |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/JSTARS.2015.2480120 | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
Keywords | Field | DocType |
Redundancy,Spatial resolution,Support vector machines,Algorithm design and analysis,Error analysis | Computer vision,Spatial dependence,Support vector machine,Remote sensing,Redundancy (engineering),Regularization (mathematics),Artificial intelligence,Real image,Self-similarity,Image resolution,Land cover,Mathematics | Journal |
Volume | Issue | ISSN |
8 | 11 | 1939-1404 |
Citations | PageRank | References |
1 | 0.35 | 17 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yihang Zhang | 1 | 86 | 8.80 |
| Feng Ling | 2 | 209 | 21.29 |
| Xiaodong Li | 3 | 171 | 16.82 |
| Yun Du | 4 | 153 | 16.11 |