Name
Title | ||
|---|---|---|
An Improved SAR Imaging Method Based on Nonconvex Regularization and Convex Optimization. |
Abstract | ||
|---|---|---|
Sparse signal processing has been applied in synthetic-aperture radar (SAR) imaging. As a typical sparse reconstruction model, L1 regularization often underestimates the intensities of the targets. The estimated radar cross section (RCS) is related to the pixel intensity. Thus, the linear relationship between the targets' intensities cannot kept. The underestimation will also cause radiometric err... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/LGRS.2019.2904520 | IEEE Geoscience and Remote Sensing Letters |
Keywords | Field | DocType |
Radar polarimetry,Image reconstruction,Synthetic aperture radar,Cost function,Estimation,Convex functions,Radar cross-sections | Iterative reconstruction,Radar,Computer vision,Synthetic aperture radar,Algorithm,Convex function,Regularization (mathematics),Artificial intelligence,Pixel,Convex optimization,Radar cross-section,Mathematics | Journal |
Volume | Issue | ISSN |
16 | 10 | 1545-598X |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhonghao Wei | 1 | 0 | 1.35 |
| Bingchen Zhang | 2 | 3 | 1.47 |
| Zhilin Xu | 3 | 1 | 2.72 |
| Bing Han | 4 | 0 | 0.68 |
| HONG Wen | 5 | 7 | 7.73 |
| Yirong Wu | 6 | 5 | 4.19 |