Name
Abstract | ||
|---|---|---|
Using sparse signal processing to replace matched filtering (MF) in synthetic aperture radar (SAR) imaging has shown significant potential to improve image quality. Due to the huge computational cost needed, it is difficult to apply conventional observation-matrix-based sparse SAR imaging method for large-scene reconstruction. The azimuth-range decouple method is able to minimize the computational... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TGRS.2018.2803802 | IEEE Transactions on Geoscience and Remote Sensing |
Keywords | Field | DocType |
Radar polarimetry,Sparse matrices,Imaging,Synthetic aperture radar,Radar imaging,Image reconstruction,Azimuth | Iterative reconstruction,Computer vision,Signal processing,Radar imaging,Pattern recognition,Synthetic aperture radar,Image quality,Filter (signal processing),Artificial intelligence,Mathematics,Sparse matrix,Computational complexity theory | Journal |
Volume | Issue | ISSN |
56 | 9 | 0196-2892 |
Citations | PageRank | References |
2 | 0.43 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hui Bi | 1 | 10 | 4.77 |
| Guoan Bi | 2 | 790 | 92.70 |
| Bing Chen Zhang | 3 | 4 | 1.19 |
| HONG Wen | 4 | 7 | 7.73 |