收稿日期: 2008-07-03
修回日期: 2008-09-22
网络出版日期: 2009-03-15
基金资助
总装预研项目(513220202) 资助
Study of improving CFAR segmentation methods from high-resolution SAR image
Received date: 2008-07-03
Revised date: 2008-09-22
Online published: 2009-03-15
陈石平 , 付琨 , 尤红建 . 高分辨率SAR图像CFAR分割的改进方法[J]. 中国科学院大学学报, 2009 , 26(2) : 230 -234 . DOI: 10.7523/j.issn.2095-6134.2009.2.012
Considering the big error and low accuracy in traditional CFAR segmentation based on Weibull model, the paper proposes the improving methods that the samples of the specific azimuth are processed using vertical median filter before segmentation and the zone growth filtering method is used to filter the noise points. The improving methods are compared with the traditional CFAR segmentation and the counting filtering by using the segmentation evaluation standards of gray-level contrast and ultimate measurement accuracy. The experimental result using the MSTRA samples demonstrates that the new methods improve the segmentation accuracy and the segmentation results are superior to the traditional CFAR segmentation methods.
Key words： segmentation; vertical median filtering; zone growth; CFAR
[1] Shyam K, Rama C. Non-Gaussian CFAR techniques for target detection in high resolution SAR images. IEEE, 1994, 1(1): 910~914
[2] Novak LM, Halversen SD. Effects of polarization and resolution on SAR ATR. IEEE Trans on Aerospace and Electronic Systems, 1997, 33(1):102~115
[3] 胡笑斌. SAR图像目标识别中几个问题的研究: . 合肥:合肥工业大学,2005
[4] 李 响,韩 萍,吴仁彪. 一种基于Weibull分布的SAR图像分割方法. 系统工程与电子技术,2007,29(5):677~679
[5] 张名成,吴秀清,王鹏伟. 一种自适应的合成孔径雷达图像目标检测方法. 计算机工程与应用,2006,42(10):200~203
[6] 王义敏,安锦文,王若朴. 基于局部双参数估计的SAR图像CFAR目标检测技术. 活力与指挥控制,2006,31(4):50~52
[7] Levine MD,Nazif A. Dynamic measurement of computer generated image segmentation. IEEE Trans PAMI, 1985, 7: 155~164
[8] Zhang YJ, Gerbrands JJ. Segmentation evaluation using ultimate measurement accuracy. SPIE, 1992, 1657: 440~460
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