摘要
针对极化合成孔径雷达(PolSAR)图像的相干斑抑制问题,提出一种快速有效的多视极化白化滤波改进算法。该算法在分块加权法的块处理基础上,采用边缘检测模板对非同质类子块进行二次分类,从而提高了多视极化白化滤波(MPWF)算法的参数估计精度。利用美国宇航局喷气推进实验室(NASA/JPL)的AIRSAR系统实测数据进行了实验,实验结果表明文中方法不仅在斑点抑制效果和运算量上优于MPWF,而且有效地克服了分块处理带来的边缘模糊问题。
In this paper,an improved algorithm of multilook polarimetric whitening filtering（MPWF） is proposed to solve the problem of speckle appearing in polarimetric synthetic aperture radar（PolSAR） images.On the basis of blocking and weighting filtering method,the new algorithm uses edge detecting template in each sub-image block to perform heterogeneous areas classification,so that more accurate PWF parameter estimation is achieved by calculating them with the classified area element values.Experimental results with polarimetric SAR real data from NASA/JPL AIRSAR system demonstrate that the proposed method is more effective both on speckle reduction and computational load compared with MPWF.It also can effectively overcome the blurry edge induced by block processing.
出处
《雷达科学与技术》
2011年第3期219-223,231,共6页
Radar Science and Technology
基金
国家自然科学基金委员会与中国民用航空局联合资助项目(No.60979002)
深圳大学ATR国防科技重点实验室开放课题
关键词
极化合成孔径雷达(PolSAR)
相干斑抑制
多视极化白化滤波
分块
边缘保持
polarimetric synthetic aperture radar（PolSAR）
speckle reduction
multilook polarimetric whitening filtering
block processing
edge preserving
