Fast Detection of Oil Spills and Ships Using SAR Images
Abstract
:1. Introduction
2. Sea Surface Model
3. Oil Spill and Ship Detection Algorithms
3.1. Image Enhancement
3.2. Oil Spill Detection
3.2.1. Image Segmentation
- Step 1: search the smaller among all of the maxima of the PDF of the data in the block under observation ();
- Step 2: estimate the derivative of the PDF to find possible saddle points;
- Step 3: sort in ascending order the value of saddle points and keep as a candidate threshold the smaller one;
- Step 4: if no saddle points are found, select as a candidate the point that is distant by one standard deviation toward the right from the maximum of the PDF;
- Step 5: memorize the candidate and repeat for every block;
- Step 6: sort all of the candidates in ascending order;
- Step 7: choose as a threshold the first candidate in ascending order whose amplitude is greater than .
3.2.2. Classification
3.2.3. Oil Spill Direction Estimation
3.3. Ship Detection
3.3.1. SAR Image Preprocessing (Wavelet Correlator)
3.3.2. S-Detector
3.3.3. W-CFAR
3.4. Ship’s Direction Estimation
- wake extraction (performed by means of segmentation algorithm with different parameters);
- DRT over four quarters of the window.
3.5. Correlation between Oil Spill and Ship
- the ship must belong to the angular sector;
- the ship’s position and direction must be consistent with the oil spill position and direction.
4. Ship-Spill Correlation Results
5. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
Abbreviations
AIS | Automatic Identification System |
CFAR | Constant False Alarm Rate |
CSK | COSMO-SkyMed |
DOAJ | Directory of Open Access Journals |
DRT | Discrete Radon Transform |
EMSA | European Maritime Safety Agency |
FEXP | Fractional EXPonential |
GEV | Generalized Extreme Value |
HH | Horizontal-Horizontal |
KDE | Kernel Density Estimation |
LRD | Long-Range Dependence |
MDPI | Multidisciplinary Digital Publishing Institute |
Probability Density Function | |
PSD | Power Spectral Density |
ROI | Region Of Interest |
RS | Radon Space |
SAR | Synthetic Aperture Radar |
SLC | Single Look Complex |
SRD | Short Range Dependence |
WCOR | Wavelet CORrelator |
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Clean sea | 0.1206 | 216.2745 |
Oil spill | 0.1580 | 100.4706 |
Clean sea | 0.3737 | 49.1312 |
Oil spill | 0.5666 | 12.8820 |
Wind fall | 1.2004 | 1.4208 |
Area | 8870 m |
Length | 228 m |
Width | 49.5 m |
Distance from the oil spill extreme | 11.23 km |
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Lupidi, A.; Staglianò, D.; Martorella, M.; Berizzi, F. Fast Detection of Oil Spills and Ships Using SAR Images. Remote Sens. 2017, 9, 230. https://doi.org/10.3390/rs9030230
Lupidi A, Staglianò D, Martorella M, Berizzi F. Fast Detection of Oil Spills and Ships Using SAR Images. Remote Sensing. 2017; 9(3):230. https://doi.org/10.3390/rs9030230
Chicago/Turabian StyleLupidi, Alberto, Daniele Staglianò, Marco Martorella, and Fabrizio Berizzi. 2017. "Fast Detection of Oil Spills and Ships Using SAR Images" Remote Sensing 9, no. 3: 230. https://doi.org/10.3390/rs9030230