摘要
给出一种基于特征分类辨识的合成孔径雷达图像目标检测方法。用恒虚警和扩展分形方法对SAR图像进行目标检测后用面积和峰值能量比算子辨识目标和背景杂波,去除一部分虚警,用小波域主成分分析对每个检测窗口内的图像提取特征向量,用支持向量机对提取得到的特征向量进行分类,辨识目标和背景杂波,完成目标检测。使用ADTS数据对该方法进行验证和分析,实验结果表明,经过特征分类辨识后,在检测率不变的情况下,虚警数目显著降低。
This paper presents a target detection method for Synthetic Aperture Radar(SAR)image based on feature classification discrimination.Constant false alarm rate and extended fractal were used to detect targets in SAR images.Area and peak power ratio operators were used to discriminate targets and background clutter for eliminating a part of false alarms.Wavelet domain principal component analysis was applied to extract feature vectors from the images within detection window.Support vector machine was applied f...
出处
《测绘学报》
EI
CSCD
北大核心
2009年第4期324-329,共6页
Acta Geodaetica et Cartographica Sinica
关键词
合成孔径雷达
检测
辨识
主成分分析
Synthetic Aperture Radar（SAR）
detection
discrimination
principal component analysis
