基于risat-1 sar数据的溢油自动检测技术研究

Pooja Shah, T. Zaveri, Raj Kumar, S. Sharma, Darshan Patel
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引用次数: 1

摘要

石油泄漏对海洋生态系统的威胁日益严重,并随着海洋运输量的增加而日益严重。在海洋中故意或意外排放的石油不仅危害海洋生态系统,而且还危害积聚的溢油以焦油的形式到达的沿海地区。从SAR数据来看,溢油检测的自动化是一个挑战。调查还发现,海洋学应用的免费和开源软件(FOSS)解决方案很少,但对于在这一领域工作的科学家来说却是必不可少的。该框架还提供了将标准数据处理算法应用于SAR数据处理的灵活性。本文介绍了一种用于C波段RISAT-1 SAR数据处理的FOSS框架。本文还对目前广泛采用的溢油检测工具的缺点进行了比较研究。描述了基于FOSS框架的超像素分割技术用于暗斑检测的实验结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research oriented foss solution for automatic oil spill detection using risat-1 sar data
Oil spill is a growing threat to marine eco-system, and it continues to grow with the growing marine traffic. Intentional or accidental oil discharges in the ocean are not limited to endangering marine eco-system but also coastal zones where the accumulated oil spill reaches as remains in form of tar. Automation of oil spill detection is challenging from SAR data. It is also surveyed that free and open source software (FOSS) solution for oceanographic applications is rare but essential for the scientists who are working in this area. Proposed FOSS framework also provides flexibility to apply standard data processing algorithms for the SAR data processing. In this paper, proposed FOSS framework to process C band RISAT-1 SAR data is described. This paper also provides the comparative study on shortcomings of the widely accepted tools for oil spill detection. The experimental results of super-pixel based segmentation technique for dark spot detection are described using proposed FOSS framework.
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