期刊文献+

SAR图像阴影区域分割技术及其评估准则 被引量:1

A SAR image shadow region segmentation method and evaluation metrics
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摘要 提出了一种阈值化技术与形态学方法相结合的SAR图像阴影区分割方法。该方法首先通过寻找图像平均强度最小的子区域对阴影区域进行初始分割,之后进行图像翻转、阈值化处理,最后利用形态学处理消除虚假像素,进行简单的连通性滤波,实现阴影区的自动分割。给出了3种图像分割评价准则,并基于计算机仿真和图像分割评价准则验证了该阴影区分割方法的有效性。 SAR imaging has shown the ability to identify targets at long ranges in adverse conditions. A recent thrust is to use the shadow information present in SAR imagery to identify the target. Clearly, it is essential to segment the shadow region from SAR image firstly. A SAR image shadow region segmentation method was presented based on morphology. The method segmented the shadow region originally. Then, morphological operations were used to perform some simple connectivity filtering to smooth the image and remove spurious pixels. And the shadow region was segmented automatically. To assess the shadow segmentation results, some target segmentation evaluation metrics were presented. The simulation results and target segmentation evaluation metrics show that the approach is effective.
出处 《海军工程大学学报》 CAS 北大核心 2009年第3期79-83,共5页 Journal of Naval University of Engineering
关键词 SAR图像 目标识别 阴影区分割 形态学 图像分割评价准则 SAR image target recognition shadow segment morphology target segmentation eva- luation metrics
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参考文献5

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二级参考文献30

  • 1Luo Tao,北京大学学报,2000年,36卷,5期,599页
  • 2Wang Junping,计算机学报,2000年,23卷,7期,673页
  • 3Lu Guanming,南京邮电学院学报,2000年,20卷,3期,51页
  • 4Zhao Haiyang,西安建筑科技大学学报,2000年,32卷,1期,43页
  • 5Dai Qingyun,中国图象图形学报,2000年,5卷,5期,411页
  • 6Huang Fenggang,中国图象图形学报,2000年,5卷,4期,89页
  • 7Cui Yi,Image Analysis Applications and Methods of Mathematical Morphology,2000年
  • 8Xu Chao,电子学报,1999年,27卷,8期,78页
  • 9Chen Huiquan,光学学报,1999年,19卷,9期,1251页
  • 10Xu Jiebin,华南理工大学学报,1999年,26卷,7期,129页

共引文献110

同被引文献16

引证文献1

二级引证文献8

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