利用方向性粗糙度特征对SAR图像目标检测的研究  

Study of Target Detection of SAR Image Using Directional Roughness Feature

作　　者：胡风明[1,2] 范学花[3] 杨汝良[1] 商建[1,2] 

机构地区：[1]中国科学院电子学研究所,北京100190 [2]中国科学院研究生院,北京100190 [3]中国科学院大气物理研究所,北京100029

出　　处：《测绘学报》2009年第3期229-235,共7页Acta Geodaetica et Cartographica Sinica

摘　　要：从反映纹理信息的粗糙度特征出发,深入研究利用方向性粗糙度特征对SAR图像进行目标检测的方法。方向性粗糙度特征是用指数小波在一个尺度上对检测图像滤波,对特定大小目标用能量关系函数求得各像素点在一个方向上的分形特征。针对MSTAR数据和ADTS数据的SAR图像,确定了用该方法检测目标时的最优参数。分别用方向性粗糙度特征和恒虚警率(CFAR)方法对上述两种不同波段的SAR图像进行目标检测,检测结果表明:方向性粗糙度特征能以更低虚警率检测出全部特定大小的目标,而且目标空间可分辨性好、位置指示准确。Based on the roughness feature indicating texture information, the method of the directional roughness feature is studied deeply for the target detection of SARimages. The directional roughness feature of each pixel can be extracted from the exponential wavelet filtered image and the energy function in one direction. The optimal parameters of the method are determined for SAR images of MSTAR and ADTS database respectively. For above two different band SAR images, the target detections are implemented by using the directional roughness feature and CFAR, The comparison of the detection results showed the directional roughness feature could not only detect all size-fixed targets but also have lower false alarm rate, higher spatial resolution and more accurate locations of the detected targets.

关 键 词：SAR 目标检测 指数小波 方向性粗糙度特征 CFAR 

分 类 号：P237[天文地球—摄影测量与遥感]