高分辨SAR图像自动区域筛选目标检测算法

宋文青; 王英华; 刘宏伟

doi:10.11999/JEIT150808

高分辨SAR图像自动区域筛选目标检测算法

doi: 10.11999/JEIT150808

基金项目:

国家自然科学基金(61201292, 61322103, 61372132)，全国优秀博士学位论文作者专项资金(FANEDD-201156)，中央高校基本科研业务费专项资金

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- 被引次数: 0
出版历程
- 收稿日期: 2015-07-08
- 修回日期: 2015-11-20
- 刊出日期: 2016-05-19

An Automatic Block-to-block Censoring Target Detector for High Resolution SAR Image

Funds:

The National Natural Science Foundation of China (61201292, 61322103, 61372132), The Foundation for the Author of National Excellent Doctoral Dissertation of China (FANEDD-201156), The Fundamental Research Funds for the Central Universities

摘要

摘要: 在G0分布背景杂波假设下，基于VI-CFAR算法该文提出一种自动区域筛选的恒虚警目标检测算法，以解决高分辨SAR图像复杂环境背景下的目标检测问题。该算法首先利用变化指数(VI)统计量对局部参考窗内的均匀区域进行筛选，以剔除参考窗内具有目标干扰点的非均匀区域；然后利用均值比(MR)统计量对参考窗内同质的均匀区域进行区域合并，以解决杂波边界处的背景杂波筛选问题；最后利用筛选到的同质均匀区域内的像素集合进行背景杂波参数估计，对待检测区域实现二值检测。通过实测SAR图像车辆目标检测实验表明，在多目标和杂波边界复杂环境背景下，该算法具有较稳定的检测性能和虚警抑制能力。
- 恒虚警检测 /
- 区域筛选 /
- 变化指数 /
- 均值比 /
- G0分布
Abstract: Assuming theG0 distribution clutter background, an automatic block-to-block censoring CFAR (ABC-CFAR) detector is proposed based on VI-CFAR for high resolution SAR image in nonhomogeneous environments. Firstly the Variability Index (VI) statistic is used to censor the blocks in the local reference window in order to reject the non-homogeneous ones in which there exists interfering target samples. Then the Mean Ratio (MR) statistic is utilized to select and combine the homogeneous blocks which have the same distribution, in order to solve background clutter censoring problem in clutter edge situation. At last, with the selected blocks, the distribution parameters of the background clutter are estimated, and then the binary detection is implemented in the Block Under Test (BUT). Using the real SAR image data including ground vehicle targets, the experimental results show that the proposed ABC-CFAR detector has robust detection performance and false alarm regulation property in multi-target and clutter edge nonhomogeneous environment.
- Block-to-block censoring /
- Variability Index (VI) /
- Mean Ratio (MR) /
- G0distribution /

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