Multi-band SAR Coherent Change Detection Method Based on Coherent Representation Differences of Targets
Ji Guangyu Dong Yongwei Bu Yuncheng Li Yanlei Zhou Liangjiang Liang Xingdong*
(Key Laboratory of Science and Technology on Microwave Imaging, Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China;University of Chinese Academy of Sciences, Beijing 100049, China)
Abstract：Coherent Change Detection (CCD) detects micro changes in a scene using phase coherence of SAR images before and after a change. It is difficult for conventional CCD method to distinguish low coherence interference region from objective change region because of a single detection scale. Multi-band SAR target detection in a multiscale way develops variable coherent representation according to the diversity of electromagnetic wave penetration, target structure, and change magnitude. In this paper, a multi-band CCD method is proposed. Firstly, the CCD images of every band were acquired; secondly, the detected scene was classified on the basis of coherent representation of targets in each single band using improved Expectation-Maximization (EM) algorithm; thirdly, the objective change class in each single band was selected by a few supervised samples; lastly, multi-band fusion CCD image was acquired by the use of Dempster-Shafer (DS) evidence theory. This multi-band CCD result can eliminate low coherent interference in each single band and decrease false alarm probability. The method is validated by L- and P-band repeat-pass SAR images acquired before and after change. Results and index parameters demonstrate the validity and correctness of the proposed method.
Preiss M and Stacy N J S. Coherent change detection:Theoretical description and experimental results[R]. DSTO-TR-1851, 2006
[2]
Jung J, Kim D J, Lavalle M, et al. Coherent change detection using InSAR temporal decorrelation model:A case study for volcanic ash detection[J]. IEEE Transactions on Geoscience and Remote Sensing, 2016, 54(10):5765-5775. DOI:10.1109/TGRS.2016.2572166
[3]
Barber J and Kogon S. Probabilistic three-pass SAR coherent change detection[C]. Proceedings of 2012 Conference Record of the Forty Sixth Asilomar Conference on Signals, Systems and Computers (ASILOMAR), Pacific Grove, California, USA, 2012:1723-1726. DOI:10.1109/ACSSC.2012.6489327
[4]
Muhuri A, Ratha D, and Bhattacharya A. Seasonal snow cover change detection over the Indian Himalayas using polarimetric SAR images[J]. IEEE Geoscience and Remote Sensing Letters, 2017, 14(12):2340-2344. DOI:10.1109/ LGRS.2017.2764123
[5]
Wahl D E, Yocky D A, Jakowatz C V, et al. A new maximum-likelihood change estimator for two-pass SAR coherent change detection[J]. IEEE Transactions on Geoscience and Remote Sensing, 2016, 54(4):2460-2469. DOI:10.1109/TGRS.2015.2502219
[6]
冷英, 李宁. 一种改进的变化检测方法及其在洪水监测中的应用[J]. 雷达学报, 2017, 6(2):204-212. DOI:10.12000/ JR16139 Leng Ying and Li Ning. Improved change detection method for flood monitoring[J]. Journal of radars, 2017, 6(2):204-212. DOI:10.12000/JR16139
[7]
An L, Li M, Zhang P, et al. Discriminative random fields based on maximum entropy principle for semisupervised SAR image change detection[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2016, 9(8):3395-3404. DOI:10.1109/JSTARS.2015.2483320
[8]
徐真, 王宇, 李宁, 等. 一种基于CNN的SAR图像变化检测方法[J]. 雷达学报, 2017, 6(5):483-491. DOI:10.12000/ JR17075 Xu Zhen, Wang Robert, Li Ning et al. A novel approach to change detection in SAR images with CNN classification[J]. Journal of radars, 2017, 6(5):483-491. DOI:10.12000/JR17075
[9]
Nielsen A A, Conradsen K, and Skriver H. Change detection in full and dual polarization, single-and multifrequency SAR data[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2015, 8(8):4041-4048. DOI:10.1109/JSTARS.2015.2416434
[10]
Nielsen A A, Conradsen K, and Skriver H. Corrections to "change detection in full and dual polarization, single-and multi-frequency SAR data"[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2017, 10(11):5143-5144. DOI:10.1109/JSTARS.2017. 2761038
[11]
Reigber A, Jäger M, and Krogager E. Polarimetric SAR change detection in multiple frequency bands for environmental monitoring in Arctic regions[C]. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Beijing, China, 2016:5702-5705. DOI:10.1109/IGARSS.2016.7730489
[12]
Li Y L, Liang X D, Zhou L J, et al.. Introduction to IECAS-SAR - A multi-frequency polarimetric airborne SAR[C]. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Quebec City, Quebec, Canada, 2014:1085-1088. DOI:10.1109/IGARSS.2014.6946617
[13]
Jackson J A and Moses R L. Feature extraction algorithm for 3D scene modeling and visualization using monostatic SAR[C]. Proceedings of SPIE 6237 Algorithms for Synthetic Aperture Radar Imagery XⅢ, Orlando, 2006, 6237:623708. DOI:10.1117/12.666558
[14]
文贡坚, 朱国强, 殷红成, 等. 基于三维电磁散射参数化模型的SAR目标识别方法[J]. 雷达学报, 2017, 6(2):115-135. DOI:10.12000/JR17034 Wen Gongjian, Zhu Guoqiang, Yin Hongcheng, et al. SAR ATR based on 3D parametric electromagnetic scattering model[J]. Journal of radars, 2017, 6(2):115-135. DOI:10.12000/JR17034
[15]
袁孝康. 星载合成孔径雷达导论[M]. 北京:国防工业出版社, 2003:234-235 Yuan Xiao-kang. Introduce to the Spaceborne Sythetic Aperture Radar[M]. Beijing:National Defense Industry Press, 2003:234-235
周智敏, 黄晓涛. VHF/UHF超宽带合成孔径雷达穿透性能分析[J]. 系统工程与电子技术, 2003, 25(11):1336-1340. DOI:10.3321/j.issn:1001-506X.2003.11.007 Zhou Zhi-min and Huang Xiao-tao. Penetration performance analysis of VHF/UHF ultra-wideband synthetic aperture radar[J]. Systems Engineering and Electronics, 2003, 25(11):1336-1340. DOI:10.3321/ j.issn:1001-506X.2003.11.007
[18]
Yin Q, Li Y, Huang P P, et al. Analysis of InSAR coherence loss caused by soil moisture variation[J]. Journal of Radars, 2015, 4(6):689-697. DOI:10.12000/JR15075
[19]
黄培康, 殷红成, 许小剑. 雷达目标特性[M]. 北京:电子工业出版社, 2005:9-62 Huang Pei-kang, Yin Hong-cheng, and Xu Xiao-jian. Radar Target Characteristics[M]. Beijing:Publishing House of Electronics Industry, 2005:9-62
[20]
冀广宇, 董勇伟, 李焱磊, 等. 一种基于概率图模型的多时相SAR相干变化检测方法[J]. 电子与信息学报, 2017, 39(12):2912-2920. DOI:10.11999/JEIT170208 Ji Guang-yu, Dong Yong-wei, Li Yan-lei, et al. A multi-temporal SAR coherent change detection method based on probabilistic graphical models[J]. Journal of Electronics & Information Technology, 2017, 39(12):2912-2920. DOI:10.11999/JEIT170208
[21]
尤红建, 付琨. 合成孔径雷达图像精准处理[M]. 北京:科学出版社, 2011:125-139 You Hong-jian and Fu Kun. Precise Processing of Synthetic Aperture Radar Images[M]. Beijing:Science Press, 2011:125-139
[22]
Touzi R, Lopes A, Bruniquel J, et al. Coherence estimation for SAR imagery[J]. IEEE Transactions on Geoscience and Remote Sensing, 1999, 37(1):135-149. DOI:10.1109/36. 739146
[23]
Anfinsen S N and Eltoft T. Application of the matrix-variate mellin transform to analysis of polarimetric radar images[J]. IEEE Transactions on Geoscience and Remote Sensing, 2011, 49(6):2281-2295. DOI:10.1109/TGRS. 2010.2103945
[24]
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. DOI:10.12000/JR15073 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. DOI:10.12000/JR15073
[25]
王桂婷, 王幼亮, 焦李成. 基于快速EM算法和模糊融合的多波段遥感影像变化检测[J]. 红外与毫米波学报, 2010, 29(5):383-388 Wang Gui-ting, Wang You-liang, and Jiao Li-cheng. Change detection method of multiband remote sensing images based on fast expectation-maximization algorithm and fuzzy fusion[J]. Journal of Infrared and Millimeter Waves, 2010, 29(5):383-388
2018, Vol. 7 
