Computer Graphics and Data Engineering, Centro de Investigación en Tecnoloxías da Información, University of Santiago de Compostela, Campus Vida, 15782 Santiago de Compostela, Spain.
Mar Pollut Bull. 2012 Oct;64(10):2090-6. doi: 10.1016/j.marpolbul.2012.07.018. Epub 2012 Aug 6.
Satellite Synthetic Aperture Radar (SAR) has been established as a useful tool for detecting hydrocarbon spillage on the ocean's surface. Several surveillance applications have been developed based on this technology. Environmental variables such as wind speed should be taken into account for better SAR image segmentation. This paper presents an adaptive thresholding algorithm for detecting oil spills based on SAR data and a wind field estimation as well as its implementation as a part of a functional prototype. The algorithm was adapted to an important shipping route off the Galician coast (northwest Iberian Peninsula) and was developed on the basis of confirmed oil spills. Image testing revealed 99.93% pixel labelling accuracy. By taking advantage of multi-core processor architecture, the prototype was optimized to get a nearly 30% improvement in processing time.
卫星合成孔径雷达（SAR）已被确立为一种检测海洋表面溢油的有用工具。已经基于这项技术开发了几种监测应用。为了更好地进行 SAR 图像分割，应该考虑风速等环境变量。本文提出了一种基于 SAR 数据和风速场估计的自适应阈值算法，以及作为功能原型一部分的实现方法。该算法适用于加利西亚海岸（伊比利亚半岛西北部）附近的一条重要航运路线，并基于已确认的溢油事件进行了开发。图像测试显示，像素标记准确率达到了 99.93%。通过利用多核处理器架构，该原型得到了优化，处理时间缩短了近 30%。
