摘要： 针对合成孔径雷达(SAR)影像相干斑噪声强烈且分布形式及参数获取困难的问题，提出一种基于独立分量分析(ICA)和序列非线性滤波(SNF)实现多极化SAR影像相干斑噪声抑制和机场目标快速提取方法。利用ICA从多极化SAR影像中自动分离出图像数据与相干斑噪声，自动选择相干斑指数最小的分量为图像分量。通过SNF从分离出的图像分量中提取出机场目标。采用ENVISAT ASAR多极化影像进行实验，结果表明该方法能快速准确地提取多极化SAR影像中的机场目标。
关键词:
极化合成孔径雷达影像,
机场目标,
自动识别,
独立分量分析,
序列非线性滤波
Abstract: A new method is proposed for speckle noise suppression and airport objects extracting from SAR imagery based on Sequential Nonlinear Filtering(SNF) and Independent Component Analysis(ICA). Speckle noise and image data are separated from multi-polarimetric imagery, and the components with the least speckle index are chosen as the object component automatically by means of ICA. Airport objects are extracted from the separated object component imagery based on sequential nonlinear filtering. Using ENVISAT ASAR polarimetric imagery, experimental results show that the proposed method can extract airport objects rapidly and accurately.
Key words:
polarimetric SAR imagery,
airport objects,
automatic recognition,
Independent Component Analysis(ICA),
Sequential Nonlinear Filtering(SNF)
中图分类号:
王 栋;陈映鹰;秦 平. 基于ICA和SNF的SAR机场目标提取[J]. 计算机工程, 2009, 35(24): 1-3.
WANG Dong; CHEN Ying-ying; QIN Ping. Airport Objects Extraction from SAR Based on ICA and SNF[J]. Computer Engineering, 2009, 35(24): 1-3.