一种基于似然比统计量的SAR相干变化检测

赵军香; 梁兴东; 李焱磊

doi:10.12000/JR16065

一种基于似然比统计量的SAR相干变化检测

DOI: 10.12000/JR16065

赵军香^①,②, ,,
梁兴东^①,,
李焱磊^①,

①.
中国科学院电子学研究所微波成像技术国家级重点实验室北京 100190
②.
中国科学院大学北京 100049

基金项目:

国家863计划船载无人机海洋观测系统 2013AA092105

国家863计划船载无人机海洋观测系统 201412002

详细信息

作者简介:
赵军香 (1989–), 女, 中国科学院电子学研究所硕士研究生, 研究方向为雷达信号处理。E-mail:jxzhao_0817@163.com

梁兴东 (1973–), 男, 中国科学院电子学研究所研究员, 研究领域包括高分辨率合成孔径雷达系统、干涉合成孔径雷达系统、成像处理及应用和实时数字信号处理。E-mail:xdliang@mail.ie.ac.cn

李焱磊 (1983–), 男, 中国科学院电子学研究所助理研究员, 研究方向为机载差分干涉SAR信号处理。E-mail:yllee@mail.ie.ac.cn

通讯作者:
赵军香, E-mail:jxzhao_0817@163.com

中图分类号: TN957.51
计量
- 文章访问数: 3048
- HTML全文浏览量: 781
- PDF下载量: 1031
- 被引次数: 0
出版历程
- 收稿日期: 2016-03-28
- 修回日期: 2016-06-15
- 网络出版日期: 2017-04-28

Change Detection in SAR CCD Based on the Likelihood Change Statistics

Zhao Junxiang^{①,②
, ,},
Liang Xingdong^{①
,},
Li Yanlei^{①
,}

①.
National Key Laboratory of Science and Technology on Microwave Imaging, Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China)
②.
University of Chinese Academy of Sciences, Beijing 100049, China)

Funds:

National 863 Plan Ship-carried UAV Ocean Observation System 2013AA092105

Surveying and Mapping Geographic Information Public Service Industry Research Projects 201412002

摘要

摘要: 相干变化检测利用相位差异可以检测出场景中的微小变化。该文针对相干变化检测中的两个问题：虚警高和阈值难选择，在原有似然比检测算法的基础上做了两点改进：运用最大似然估计优化似然比统计量中的参数，并采用邻域滑动窗口使得参数估计结果更加准确稳健；根据差异图像直方图提出了一种基于邻域直方图差的自动阈值选取方法。实测数据处理结果验证了算法的有效性。
- 合成孔径雷达 /
- 相干变化检测 /
- 似然比 /
- 自动阈值
Abstract: The Coherent Change Detection (CCD) measures the phase difference in repeat passes in SAR images and is a powerful technique for detecting minute changes between two synthetic aperture radar images taken at different times. Nevertheless, the CCD has two problems. These are the high false-alarm rates and threshold selection. To deal with these problems using the likelihood change, this study makes two improvements. First, the model parameters are optimized by the maximum likelihood method and more accurate and robust parameters are obtained by using the sliding window in the neighborhood operations. Second, the automatic change in the threshold method is proposed based on the histogram characteristics of different data. The processing of real data suggests that the proposed method is effective in detecting minute changes.
- Synthetic Aperture Radar (SAR) /
- Coherent Change Detection (CCD) /
- Likelihood ratio /
- Automatic threshold

HTML全文

图 1 ROC曲线

Figure 1. ROC curves

下载: 全尺寸图片幻灯片

图 2 窗口的选择

Figure 2. Two different windows

下载: 全尺寸图片幻灯片

图 3 基于似然比变化检测的流程图

Figure 3. A change detection based on the likelihood change statistic for SAR CCD

下载: 全尺寸图片幻灯片

图 4 理想中差异图像的直方图

Figure 4. Ideal histogram of likelihood change statistic

下载: 全尺寸图片幻灯片

图 5 实测数据得到的差异影像直方图

Figure 5. Histogram of likelihood change statistic

下载: 全尺寸图片幻灯片

图 6 自动阈值选取方法

Figure 6. The results of automatic threshold selection

下载: 全尺寸图片幻灯片

图 7 地面真实变化

Figure 7. Ground truth observations of the changed scene

下载: 全尺寸图片幻灯片

图 8 估计全局协方差矩阵的样本

Figure 8. The sample data for estimation of the covariance matrixes

下载: 全尺寸图片幻灯片

图 9 检测结果

Figure 9. Detection results

下载: 全尺寸图片幻灯片

图 10 三种算法的ROC曲线

Figure 10. Experimental ROC curves of the three change detection method

下载: 全尺寸图片幻灯片

表 1 LLR_CCD方法和CCD方法的性能指标

Table 1. Results of change detection by CCD and LLR_CCD

性能评估参数	LLR_CCD			CCD
性能评估参数	本文阈值选取方法	OSTU	手动最佳阈值	本文阈值选取方法	OSTU	手动最佳阈值
阈值	–104.83	72.06	–125	0.77	0.71	0.32
检测率P_TP	0.7281	1	0.6641	1	0.9984	0.5703
负检率P_TN	0.9965	0.3811	0.9989	0.8737	0.9134	0.9933
虚警率P_FP	0.0035	0.6189	0.0011	0.1263	0.0866	0.0067
漏检率P_FN	0.2719	0	0.3359	0	0.0016	0.4297
Kappa	0.7454	0.0193	0.7626	0.1811	0.2517	0.5684

下载: 导出CSV

参考文献(16)

[1]	Corr D G. Coherent change detection for urban development monitoring[C]. IEE Colloquium on Radar Interferometry, 1997: 1-6. doi: 10.1049/ic:19970856.
[2]	Corr D G and Rodrigues A. Coherent change detection of vehicle movements[C]. 1998 IEEE International Geoscience and Remote Sensing Symposium Proceedings, Seattle, WA, 1998, 5: 2451-2453.
[3]	Preiss M and Stacy N J S. Coherent change detection: theoretical description and experimental results[R]. Defence Science and Technology Organisation, 2006.
[4]	Johnsen T. Coherent change detection in SAR images of harbors with emphasis on findings from container backscattering[C]. IEEE National Radar Conference, Kansas City, MO, 2011: 118-123.
[5]	Milisavljević N, Closson D, and Bloch I. Detecting potential human activities using coherent change detection[C]. International Conference on Image Processing Theory Tools and Applications (IPTA), Paris, 2010: 482-485.
[6]	曾晓燕. 极化SAR图像配准与相干变化检测方法研究[D]. [硕士论文], 电子科技大学, 2010. Zeng Xiao-yan. Study of registration and coherent change detection in polarization SAR images[D]. [Master dissertation], University of Electronic Science and Technology of China, 2010.
[7]	宣延艳. 极化SAR相干信息配准与变化检测算法研究[D]. [硕士论文], 电子科技大学, 2011. http://cdmd.cnki.com.cn/Article/CDMD-10614-1011191892.htm Xuan Yan-yan. Coherent information registration and change detection in polarization SAR[D]. [Master dissertation], University of Electronic Science and Technology of China, 2011. http://cdmd.cnki.com.cn/Article/CDMD-10614-1011191892.htm
[8]	Liao M, Jiang L, Lin H, et al.. Urban change detection based on coherence and intensity characteristics of SAR imagery[J]. Photogrammetric Engineering & Remote Sensing, 2008, 74(8): 999-1006. https://www.researchgate.net/publication/273663116_Urban_Change_Detection_Based_on_Coherence_and_Intensity_Characteristics_of_SAR_Imagery
[9]	杨祥立, 徐德伟, 黄平平, 等.融合相干/非相干信息的高分辨率SAR图像变化检测[J].雷达学报, 2015, 4(5): 582-590. http://radars.ie.ac.cn/CN/abstract/abstract298.shtml Yang Xiang-li, Xu De-wei, Huang Ping-ping, et al.. Change detection of high resolution SAR images by the fusion of coherent/incoherent information[J]. Journal of Radars, 2015, 4(5): 582-590. http://radars.ie.ac.cn/CN/abstract/abstract298.shtml
[10]	Preiss M, Gray D A, and Stacy N J S. Detecting scene changes using synthetic aperture radar interferometry[J]. IEEE Transactions on Geoscience & Remote Sensing, 2006, 44(8): 2041-2054. https://www.researchgate.net/publication/3204158_Detecting_scene_changes_using_synthetic_aperture_Radar_interferometry
[11]	Wright P, Macklin T, Willis C, et al.. Coherent change detection with SAR[C]. Radar Conference, Paris, 2005: 17-20.
[12]	Phillips R D. Clean: a false alarm reduction method for SAR CCD[C]. IEEE International Conference on Acoustics, Prague, 2011: 1365-1368.
[13]	Yu B and Phillips R D. Multispectral vegetation detection for improved SAR CCD[C]. IEEE Conference Record of the Forty Sixty Asilomar, Pacific Grove, CA, 2012: 1664-1668.
[14]	Yu B and Phillips R D. Using contextual information to improve SAR CCD: Bayesian contextual coherent change detection (BC CCD)[C]. IEEE International Geoscience & Remote Sensing Symposium (IGARSS), Quebec City, 2014: 1277-1280.
[15]	谢凤英, 赵丹培. Visual C++数字图像处理[M].北京:电子工业出版社, 2008: 279-290. Xie Feng-ying and Zhao Dan-pei. Visual C++ Digital Image Processing[M]. Beijing: Publishing House of Electronics Industry, 2008: 279-290.
[16]	熊博莅. SAR图像配准及变化检测技术研究[D]. [博士论文], 国防科学技术大学, 2012. http://cdmd.cnki.com.cn/Article/CDMD-90002-1013047531.htm Xiong Bo-li. Study of registration and change detection in SAR images[D]. [Ph.D. dissertation], Graduate School of National University of Defense Technology, 2012. http://cdmd.cnki.com.cn/Article/CDMD-90002-1013047531.htm