Name
Abstract | ||
|---|---|---|
It is very difficult to detect oil spills when the scattering intensity of background clutter is inhomogeneous in synthetic aperture radar (SAR) images. To improve the oil detection capability, we propose a modified constant false alarm rate (CFAR)-based method for the detection of oil spills in SAR images. This proposed method combines edge detection technique and CFAR detection theory to improve the accuracy of oil spills detection. First, we segment the image into the areas of interest (AOIs) by using ratio edge detection. Second, to get a more accurate detection result, an improved Weibull-CFAR detector is applied to these AOIs. Experimental results demonstrate that the modified CFAR algorithm can work more effectively than a global CFAR detector for oil spill detection, especially for the inhomogeneous intensity SAR images. This model can detect the target more effectively, and false alarms can be greatly diminished. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1080/10798587.2014.960228 | INTELLIGENT AUTOMATION AND SOFT COMPUTING |
Keywords | Field | DocType |
CFAR, Oil spill detection, Ratio edge detection, SAR | Computer vision,Oil spill,Detection theory,Clutter,Computer science,Synthetic aperture radar,Edge detection,Algorithm,Cfar detector,Artificial intelligence,Constant false alarm rate,Detector | Journal |
Volume | Issue | ISSN |
21 | 2 | 1079-8587 |
Citations | PageRank | References |
0 | 0.34 | 19 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Siyuan Wang | 1 | 0 | 1.01 |
| Xingyu Fu | 2 | 9 | 2.22 |
| yan zhao | 3 | 12 | 5.00 |
| Hui Wang | 4 | 0 | 0.68 |