Adaptive Enhancement of X-Band Marine Radar Imagery to Detect Oil Spill Segments

作     者：Liu, Peng Li, Ying Xu, Jin Zhu, Xueyuan 

作者机构：Dalian Maritime Univ Environm Informat Inst Nav Coll Dalian 116026 Peoples R China 

出 版 物：《SENSORS》 (Sensors)

年 卷 期：2017年第17卷第10期

页      面：2349页

核心收录：

学科分类：0710[理学-生物学] 071010[理学-生物化学与分子生物学] 0808[工学-电气工程] 07[理学] 0804[工学-仪器科学与技术] 0703[理学-化学] 

基　　金：Marine Public Welfare Projects of China National Natural Science Foundation 

主　　题：X-band marine radar oil spill detection adaptive algorithm 

摘      要：Oil spills generate a large cost in environmental and economic terms. Their identification plays an important role in oil-spill response. We propose an oil spill detection method with improved adaptive enhancement on X-band marine radar systems. The radar images used in this paper were acquired on 21 July 2010, from the teaching-training ship YUKUN of the Dalian Maritime University. According to the shape characteristic of co-channel interference, two convolutional filters are used to detect the location of the interference, followed by a mean filter to erase the interference. Small objects, such as bright speckles, are taken as a mask in the radar image and improved by the Fields-of-Experts model. The region marked by strong reflected signals from the sea s surface is selected to identify oil spills. The selected region is subject to improved adaptive enhancement designed based on features of radar images. With the proposed adaptive enhancement technique, calculated oil spill detection is comparable to visual interpretation in accuracy.