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计算机工程 ›› 2009, Vol. 35 ›› Issue (24): 1-3.doi: 10.3969/j.issn.1000-3428.2009.24.001

• 博士论文 •    下一篇

基于ICA和SNF的SAR机场目标提取

王 栋1，陈映鹰1,2，秦 平3   

  1. (1. 同济大学测量与国土信息工程系，上海 200092；2. 同济大学遥感空间信息技术研究中心，上海 200092；3. 国家海洋局东海预报中心，上海 200082)
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2009-12-20 发布日期:2009-12-20

Airport Objects Extraction from SAR Based on ICA and SNF

WANG Dong1, CHEN Ying-ying1,2, QIN Ping3   

  1. (1. Dept. of Surveying and Geo-informatics, Tongji University, Shanghai 200092; 2. Research Center for Remote Sensing and Spatial Information, Tongji University, Shanghai 200092; 3. East China Sea Marine Prediction Center, State Bureau of Oceanic Administration, Shanghai 200082)
  • Received:1900-01-01 Revised:1900-01-01 Online:2009-12-20 Published:2009-12-20

PDF

1460

被引次数

11 | 6

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)

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