Sea Surface Oil Spill Detection Based on CFAR
基于CFAR海上溢油检测研究

A novel method is presented for oil spill detection in synthetic aperture radar (SAR) images,which is based on the constant false alarm rate (CFAR) technique and considers the probability density function of sea clutter as Gaussian distribution.All possible oil spills are detected using an overall threshold,which is calculated using the analytic formula.Then a statistic filter is used to eliminate the false oil spill pixels.This method avoids complicated iteration,calculation of shape parameters and dichotomy threshold,and therefore its accuracy and computation speed are improved,which are demonstrated by the results.In the paper,the main techniques for oil spill detection in SAR images are reviewed.A novel method is presented,which is based on CFAR technique and Gaussian distribution of sea surface clutter.In this method,CFAR operator is given based on Gaussian distribution (normal distribution),and the statistic filter is introduced to eliminate the false oil spill pixels,finally the framework of the method is described.The ASAR images are used for the algorithm test.Parameters such as detection threshold,computation time,etc.Results and comparison show that the new method proposed in this paper has advantages of high accuracy and computation speed.