Name
Abstract | ||
|---|---|---|
In synthetic aperture radar (SAR) imagery, relating to maritime surveillance studies, the ship has always been the main focus of study. In this letter, a method of ship classification in SAR images is proposed to enhance classification accuracy. In the proposed method, to fully exploit the distinguishing characters of the ship targets, both topology and intensity of the scattering points of the ship are considered. The results of testing the proposed method on a data set of three types of ships, collected via a space-borne SAR sensor designed by the Institute of Electronics, Chinese Academy of Sciences (IECAS), establish that the proposed method is superior to several existing methods, including the original shape contexts method, traditional invariant moments and the recent approach. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.3390/rs9020145 | REMOTE SENSING |
Keywords | Field | DocType |
ship classification,improved shape contexts,scattering centers,synthetic aperture radar (SAR) image | Computer vision,Synthetic aperture radar,Remote sensing,Chinese academy of sciences,Exploit,Electronics,Artificial intelligence,Invariant (mathematics),Geology | Journal |
Volume | Issue | ISSN |
9 | 2 | 2072-4292 |
Citations | PageRank | References |
2 | 0.37 | 15 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jiwei Zhu | 1 | 2 | 0.37 |
| Xiaolan Qiu | 2 | 190 | 26.75 |
| Zongxu Pan | 3 | 74 | 8.13 |
| Yueting Zhang | 4 | 3 | 2.07 |
| Bin Lei | 5 | 11 | 4.73 |