摘要
利用极化白化滤波(PWF)算法融合Envisat/ASAR双极化复数据图像,同时抑制相干斑,然后利用双参数恒虚警率(2pCFAR)算法进行舰船目标检测。在不同检测门限和检测模板条件下,利用实测VV/HV极化组合数据进行的仿真实验结果表明,联合PWF-2pCFAR算法不仅能够有效地检测出舰船目标,较好地降低了虚警率,也能够保留舰船目标的结构信息;同时得到了一组相对最优的检测门限与检测模板,具有一定的实际参考意义。
Dual-polarimetric-channel complex images of Envisat/ASAR are firstly processed into an intensity image using a polarimetric whitening filter （PWF）. Then a two-parameter constant false alarm rate （2pCFAR） detector is run over the image to detect the ships. The simulation experiments with various detection thresholds and detection stencils are carried out using complex data of Envisat/ASAR VV/HV configuration in the paper. The results show that the combined PWF-2pCFAR algorithm can effectively detect ships with a low FAR and preserve the structure information of them. Besides, a group of both detection threshold and detection stencil to produce a better detection performance is obtained, offering a practical reference for the ship detection using Envisat/ASAR dual polarization data.
出处
《信息工程大学学报》
2008年第3期319-322,共4页
Journal of Information Engineering University
基金
军队科研基金资助项目
