Name
Abstract | ||
|---|---|---|
A methodology for change detection of artificial features using multitemporal series of SAR data is presented. The methodology uses time averaging of data from ERS-2 and Envisat yielding improved radiometric quality which highly improves the photointerpretability. The methodology is tested in several scenarios in the context of security applications when data needs to he gathered during cloudy season when optical satellites are unable operate. The results have been validated with very high resolution optical data from summer season. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/IGARSS.2007.4423210 | IGARSS: 2007 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-12: SENSING AND UNDERSTANDING OUR PLANET |
Keywords | Field | DocType |
SAR, multitemporal filtering, superresolution, change detection | Computer vision,Satellite,Change detection,Computer science,Synthetic aperture radar,Remote sensing,Filter (signal processing),Feature extraction,Radiometry,Artificial intelligence,Image resolution,Adaptive optics | Conference |
ISSN | Citations | PageRank |
2153-6996 | 0 | 0.34 |
References | Authors | |
1 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rosana Romero | 1 | 0 | 0.34 |
| Jesus Sanz-Marcos | 2 | 137 | 15.03 |
| Daniel Carrasco | 3 | 0 | 0.34 |
| Victoriano Moreno | 4 | 0 | 0.68 |
| Juan Luis Valero | 5 | 0 | 0.34 |
| Marc Lafitte | 6 | 0 | 0.34 |