Name
Abstract | ||
|---|---|---|
In this paper, we introduce two spatially adaptive filtering methods to improve the estimation of the covariance matrix (CM), which is required for the processing of tomographic SAR data. We evaluate their effect on scatterer separation and height estimation. We propose several criteria to evaluate such methods and introduce a spatial simulation procedure allowing generating a tomographic image st... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TGRS.2017.2746420 | IEEE Transactions on Geoscience and Remote Sensing |
Keywords | Field | DocType |
Estimation,Tomography,Solid modeling,Synthetic aperture radar,Speckle,Three-dimensional displays,Adaptation models | Computer vision,Tomographic reconstruction,Estimation of covariance matrices,Synthetic aperture radar,Filter (signal processing),Algorithm,Smoothing,Adaptive filter,Artificial intelligence,Layover,Covariance matrix,Mathematics | Journal |
Volume | Issue | ISSN |
56 | 1 | 0196-2892 |
Citations | PageRank | References |
0 | 0.34 | 23 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Olivier D'Hondt | 1 | 41 | 6.01 |
| Carlos López-Martínez | 2 | 0 | 2.03 |
| S. Guillaso | 3 | 29 | 3.59 |
| Olaf Hellwich | 4 | 185 | 37.01 |