A fast, edge-preserving, distance-regularized model with bilateral filtering for oil spill segmentation of SAR images

Wandi WANG; Hui SHENG; Yanlong CHEN; Shanwei LIU; Jijun MAO; Zhe ZENG; Jianhua WAN

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A fast, edge-preserving, distance-regularized model with bilateral filtering for oil spill segmentation of SAR images

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Marine oil spills are among the most significant sources of marine pollution.Synthetic aperture radar(SAR)has been used to improve oil spill observations because of its advantages in oil spill detection and identification.However,speckle noise,weak boundaries,and intensity inhomogeneity often exist in the oil spill regions of SAR imagery,which will seriously aff ect the accurate identification of oil spills.To enhance marine oil spill segmentation of SAR images,a fast,edge-preserving framework based on the distance-regularized level set evolution(DRLSE)model was proposed.Specifically,a bilateral filter penalty term is designed and incorporated into the DRLSE energy function(BF-DRLSE)to preserve the edges of oil spills,and an adaptive initial box boundary was selected for the DRLSE model to reduce the operation time complexity.Two sets of RadarSat-2 SAR data were used to test the proposed method.The experimental results indicate that the bilateral filtering scheme incorporated into the energy function during level set evolution improved the stability of level set evolution.Compared with other methods,the proposed improved BF-DRLSE algorithm displayed a higher overall segmentation accuracy(97.83%).In addition,using an appropriate initial box boundary for the DRLSE method accelerated the global search process,improved the accuracy of oil spill segmentation,and reduced computational time.Therefore,the results suggest that the proposed framework is eff ective and applicable for marine oil spill segmentation.

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《中国海洋湖沼学报（英文版）》 |2021年第4期|1198-1210|共13页
作者
Wandi WANG; Hui SHENG; Yanlong CHEN; Shanwei LIU; Jijun MAO; Zhe ZENG; Jianhua WAN;
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作者单位

China University of Petroleum Qingdao 266580 China;

China University of Petroleum Qingdao 266580 China;

China University of Petroleum Qingdao 266580 China;

National Marine Environmental Monitoring Centre Dalian 116023 China;

China University of Petroleum Qingdao 266580 China;

Surveying and Mapping Institute of Shandong Province Jinan 250102 China;

China University of Petroleum Qingdao 266580 China;

China University of Petroleum Qingdao 266580 China;

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A fast, edge-preserving, distance-regularized model with bilateral filtering for oil spill segmentation of SAR images

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