摘要
利用合成孔径雷达(SAR)可在日夜及全天候条件下进行高分辨率溢油监测的优点,提出了一种基于特征向量的SAR图像溢油识别方法。在暗区边界确定的SAR图像中进行量算,得到特征向量,并采用Mahalanobis距离对目标物进行识别。经实验验证,选取的特征值数量合理,且对于判定是否为溢油效果明显;利用Mahalanobis距离进行判别,算法清晰,且准确率达到96%以上;与其他溢油判定方法相比,附加条件较少,且利于在计算机上编程实现。
A method on feature vector of the oil spills identification in SAR images is proposed,The advantages of Synthetic Aperture Radar（SAR） are useful,which can work on day and night and all weather conditions for high resolution monitoring of oil spills.The Mahalanobis distance approach has been developed in order to evaluate the probability that a dark area is a slick on SAR images.The experimental verification,a small number of characteristic values has been selected in the paper for that oil spills is significant.The algorithm of Mahalanobis distance discrimination is clear,and the accuracy rate reaches 96% or more.Compare to other oil spills determine methods,this approach appends less conditions and is conducive to computer programming.
出处
《计算机工程与应用》
CSCD
北大核心
2011年第18期195-197,203,共4页
Computer Engineering and Applications
