A novel multi-level segmentation method on oil spill of SAR image

Yue Guo; XiaoFeng Wang

doi:10.1117/12.920203

13 January 2012 A novel multi-level segmentation method on oil spill of SAR image

Yue Guo, XiaoFeng Wang

Proceedings Volume 8349, Fourth International Conference on Machine Vision (ICMV 2011): Machine Vision, Image Processing, and Pattern Analysis; 83490B (2012) https://doi.org/10.1117/12.920203
Event: Fourth International Conference on Machine Vision (ICMV 11), 2011, Singapore, Singapore

Abstract

Using SAR to monitor oil spill is a useful method. As the performance of oil spill on SAR images is similar with other oceanic phenomenon, it is difficult to distinguish between oil spill and "look-alikes". This paper presents a novel multi- level method to extract the oil film from original SAR image. The method can retain original edge information of oil film while separated it from the background. This paper applied lee filter, fuzzy c means, coherence filter and morphological operations to de-noise and segment SAR image. Experimental results show that the method can not only distinguish oil film and the sea, but revert part of edge information lost in the process of de-noising and the segmentation.

Citation Download Citation

Yue Guo and XiaoFeng Wang "A novel multi-level segmentation method on oil spill of SAR image", Proc. SPIE 8349, Fourth International Conference on Machine Vision (ICMV 2011): Machine Vision, Image Processing, and Pattern Analysis, 83490B (13 January 2012); https://doi.org/10.1117/12.920203

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