Name
Abstract | ||
|---|---|---|
Since the ship wakes appear in SAR images as dark/bright lines, they are typically identified by using line detectors, such as the Radon Transform. The most assessed techniques imply the thresholding approach in the Radon domain in order to recognize peaks and troughs representative of ship features. In this ambit, the paper shows an application of an original approach for wake detection in high-resolution SAR images, conceived to be adequate for inclusion in an automatic maritime surveillance procedure. In the proposed algorithm, the peaks/troughs are detected and recognized as representative of the ship wakes only if their appearance is compatible with the physical characteristics of the wakes provided by the hydrodynamic theory. In order to estimate its performance, it is applied on 11different wake appearances imaged in the Gulf of Naples by 3 passages of COSMO/SkyMed and one passage of TerraSAR-X in stripmap working mode under different polarizations. The results show that the proposed algorithms well recognizes the wake features, also in scenarios with very close wakes or with land and azimuth ambiguities bright returns. |
Year | Venue | Keywords |
|---|---|---|
2015 | 2015 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | One, two, three, four, five |
Field | DocType | ISSN |
Wake,Computer vision,Radar imaging,Computer science,Synthetic aperture radar,Early-warning radar,Remote sensing,Azimuth,Inverse synthetic aperture radar,Artificial intelligence,Thresholding,Radon transform | Conference | 2153-6996 |
Citations | PageRank | References |
0 | 0.34 | 4 |
Authors | ||
1 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Maria Daniela Graziano | 1 | 8 | 6.37 |