Journal of Geo-information Science >
Dual-threshold Oil Spills Detection Based on Characteristic Possibility Function
Received date: 2011-09-15
Revised date: 2012-07-14
Online published: 2012-08-22
Supported by
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Oil spills can cause huge damage to the ecology of marine environment and its detection and clean-up plays a very important role in the reduction of economic and environmental losses. As an advanced technology, synthetic aperture radar (SAR) has the advantage of day-night all weather observation capability. Besides, SAR has relatively wide swath width and high resolution, which all helps a lot in the early warning and damage analysis of oil spills accidents. Due to the special imaging mechanism of SAR, oil spills can be found as dark spots in SAR images. However, there still remain a lot of difficulties in the related detection and classification algorithms. In this paper, a double-threshold oil spills detection based on characteristic possibility function was proposed for taking the best advantages of backscatter information contained in different grayscale levels. Both high and low levels of grayscale information were extracted from the backscatter image obtained from SAR signal. Then the density of pixels was evaluated by Gauss kernel to enhance the stability of the segmentation. By using high level segmentation result, look-alikes with large area are classified from oil spills by basic morphological analysis. By taking advantage of low threshold grayscale information, other look-alikes were distinguished from oil spills by means of probability likelihood function derived from morphological characters such as complexity, length to width ratio, Euler number, etc.. Finally, the detected spills were obtained by fusing classification result of different level and other auxiliary information. The proposed method was implemented on EVISAT ASAR images of coastal region around Hong Kong received by the satellite ground station, CUHK. Experimental results demonstrated that real oil spills and look-alikes generated by other natural phenomena such as low wind speed and internal water turbulence could be distinguished accurately and effectively. This method can be further developed and has potential use in the surveillance and early alarm of marine and coastal oil leak accidents.
Key words： SAR imagery; dark spot extraction; oil spill detection; classification
LI Yu, ZHANG Yuanzhi*, Chen Jie . Dual-threshold Oil Spills Detection Based on Characteristic Possibility Function[J]. Journal of Geo-information Science, 2012 , 14(4) : 531 -539 . DOI: 10.3724/SP.J.1047.2012.00531
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