Abstract

Oil spills generate a large cost in environmental and economic terms. Their identification plays an important role in oil-spill response. We propose an oil spill detection method with improved adaptive enhancement on X-band marine radar systems. The radar images used in this paper were acquired on 21 July 2010, from the teaching-training ship “YUKUN” of the Dalian Maritime University. According to the shape characteristic of co-channel interference, two convolutional filters are used to detect the location of the interference, followed by a mean filter to erase the interference. Small objects, such as bright speckles, are taken as a mask in the radar image and improved by the Fields-of-Experts model. The region marked by strong reflected signals from the sea’s surface is selected to identify oil spills. The selected region is subject to improved adaptive enhancement designed based on features of radar images. With the proposed adaptive enhancement technique, calculated oil spill detection is comparable to visual interpretation in accuracy.

Highlights

  • Oil spills are one of the major environmental hazards in ocean basins

  • For our purpose, no additional radars have to be purchased and the radar images are available on the navigation radar

  • Compared with other oil spill detection methods, such as laser fluorescence [8], optical sensors [9], and SAR [10], which call for specialized devices or expensive satellite images in the contingency plan, marine radars are more convenient, expedient, and economical

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Summary

Introduction

Oil spills are one of the major environmental hazards in ocean basins. According to studies of Alves et al in the Mediterranean Basin [1,2,3,4,5], in oil spill accidents, crude oil at, and beneath, the water’s surface can quickly spread and reach the coastline under particular weather and oceanographic conditions. 2017, 17, 2349number of images to calculate the attenuation of the signal intensity, which of 14 affected by the ship’s location and direction. Another drawback lies in its overall estimated the oil spills. Since different strip thicknesses render different segmentation results, the final oil spill area is adaptive enhancement will be compared with methods proposed in Bradley et al and Zhu et al. The proposed improved adaptive enhancement will be compared with methods proposed in Bradley et al and Zhu et al Section 5 is the conclusion

Radar Image Collection
Co-Channel shown the in Figure
Data processing co-channel
Small Objects
Regions Selected for the Current Study
As shown
Figure
Adaptive Enhancement to Detect Oil Spill
Evaluation of of the the Improved
Conclusions
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