| 高分辨率SAR图像CFAR分割的改进方法 |
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| 作者姓名： | 陈石平 付琨 尤红建 |
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| 作者单位： | 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 100049 |
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| 基金项目： | 总装预研项目(513220202) 资助 |
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| 摘 要： | 针对传统的基于韦布尔模型的恒虚警检测(CFAR)分割中误差大、精度低的缺点,提出了分割前对特定方向角样本进行垂直中值滤波、分割后采用区域生长滤波的改进方法.最后用区域间对比度和最终测量精度的分割评价准则,与传统CFAR分割和计数滤波的方法进行了比较.对运动和静止目标获取和识别(MSTAR)样本的实验结果表明,改进方法提高了分割精度,分割效果优于传统的CFAR分割方法.
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| 关 键 词： | 分割 垂直中值滤波 区域生长 恒虚警检测 |
| 收稿时间： | 2008-07-03 |
| 修稿时间： | 2008-09-22 |
Study of improving CFAR segmentation methods from high-resolution SAR image |
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| Authors: | CHEN Shi-Ping FU Kun YOU Hong-Jian |
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| Institution: | 1. Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China;
2. Graduate University of the Chinese Academy of Sciences, Beijing 100049, China |
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| Abstract: | 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. |
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| Keywords: | segmentation vertical median filtering zone growth CFAR |
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