Oil spill detection in Radarsat and Envisat SAR images

被引：232

作者：

Solberg, Anne H. S. ^{[1
]}

Brekke, Camilla

Husoy, Per Ove

机构：

[1] Univ Oslo, Dept Informat, N-0316 Oslo, Norway

[2] Norwegian Comp Ctr, N-0316 Oslo, Norway

[3] Norwegian Def Res Estab, N-2027 Kjeller, Norway

[4] Univ Oslo, Dept Informat, N-0314 Oslo, Norway

[5] Norwegian Comp Ctr, N-0314 Oslo, Norway

来源：

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING | 2007年 / 45卷 / 03期

关键词：

classification; feature extraction; oil spill detection; synthetic aperture radar (SAR);

D O I：

10.1109/TGRS.2006.887019

中图分类号：

P3 [地球物理学]; P59 [地球化学];

学科分类号：

0708 ; 070902 ;

摘要：

We present algorithms for automatic detection of oil spills in synthetic aperture radar (SAR) images. The algorithms consist of three main parts, namely: 1) detection of dark spots; 2) feature extraction from the dark spot candidates; and 3) classification of dark spots as oil spills or look-alikes. The algorithms have been trained on a large number of Radarsat and Envisat Advanced Synthetic Aperture Radar (ASAR) images. The perform mance of the algorithm is compared to manual and semiautomatic approaches in a benchmark study using 59 Radarsat and Envisat images. The algorithms can be considered to be a good alternative to. manual inspection when large ocean areas are to be inspected.

引用

页码：746 / 755

页数：10

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