摘要
结合区域划分和结构检测模板提出了改进极化白化滤波(IPW F)算法,利用IPW F算法融合极化合成孔径雷达(POL-SAR)中各极化通道图像,同时抑制相干斑,然后利用双参数恒虚警率(CFAR)检测方法对融合后的图像进行船舶目标检测.本文利用香港地区S IR-C全极化单视复数据进行了实验,结果表明IPW F算法更好地降低了相干斑因子,提高了船舶目标的检测率、控制了虚警率,同时可以更好地保持船舶目标的结构信息.
An improved polarimetric whitening filter （IPWF） algorithm is proposed by combining an area classification procedure and structure detection models. It is applied to fuse images of different polarimetric channels in polarimetric synthetic aperture radar （POL-SAR） and reduce speckle noise, and then the two-parameter Constant False Alarm Rate （CFAR） method is applied on the fused images to detect the ship targets. Experimental results using SIR-C polarimetric Single-Look Complex data in Hong Kong area demonstrate that the IPWF algorithm can reduce the speckle, enhance the detection rate, control the false alarm rate （FAR） and preserve the structure information of ship targets.
出处
《测试技术学报》
2006年第1期65-70,共6页
Journal of Test and Measurement Technology
基金
微波成像技术国家重点实验室基金(51442020105ZS2002)
