合成孔径雷达图像舰船尾迹检测算法

doi:10.16183/j.cnki.jsjtu.2019.311

上海交通大学学报 ›› 2020, Vol. 54 ›› Issue (12): 1259-1268.doi: 10.16183/j.cnki.jsjtu.2019.311

合成孔径雷达图像舰船尾迹检测算法

赵婷¹, 王申涛¹, 牛林¹, 席沛丽², 蔡云泽¹()

^1.上海交通大学　自动化系；系统控制与信息处理教育部重点实验室；海洋智能装备与系统教育部实验室，上海　200240
^2.上海卫星工程研究所，上海　201109

收稿日期:2019-10-29 出版日期:2020-12-01 发布日期:2020-12-31
通讯作者: 蔡云泽 E-mail:yzcai@sjtu.edu.cn
作者简介:赵婷(1995-)，女，山西省运城市人，硕士生，从事图像处理等研究．
基金资助:
国家科技重大专项(2018YFB1305003);国家自然科学基金(61627810);上海航天科技创新基金(SAST2015007);航天先进技术联合研究中心基金(USCAST2015-11);中国先进航空航天制造技术研究联合基金(USCAST2016-2)

Detection Algorithm of Ship Wake in SAR Images

ZHAO Ting¹, WANG Shentao¹, NIU Lin¹, XI Peili², CAI Yunze¹()

^1.Department of Automation; Key Laboratory of System Control and Information Processing of the Ministry of Education; Key Laboratory of Marine Intelligent Equipment and System of the Ministry of Education, Shanghai Jiao Tong University, Shanghai 200240, China
^2.Shanghai Institute of Satellite Engineering, Shanghai 201109, China

Received:2019-10-29 Online:2020-12-01 Published:2020-12-31
Contact: CAI Yunze E-mail:yzcai@sjtu.edu.cn

摘要/Abstract

摘要：

针对合成孔径雷达(SAR)图像舰船尾迹检测问题，提出了基于解析字典的相干斑噪声抑制算法和基于Radon变换的尾迹检测算法．首先，利用基于解析字典的形态成分分离算法对SAR图像进行成分分离，得到含有舰船尾迹的结构成分图像和含有相干斑噪声及海杂波的纹理成分图像．然后，对包含舰船尾迹的结构成分进行局部Radon变换，并通过基于峰值聚类决策的舰船尾迹识别算法对真假局部峰值点进行判别，得到真实尾迹产生的局部峰值点，确定舰船尾迹的具体位置．实验结果表明，该算法能有效地完成SAR图像舰船尾迹检测．

关键词: 合成孔径雷达图像, 舰船尾迹, 乘性噪声去噪, 稀疏表示, Radon变换

Abstract:

In order to solve the problem of ship wake detection in synthetic aperture radar (SAR) image, a coherent speckle noise suppression algorithm based on analytic dictionary and a wake detection algorithm based on Radon transform are proposed. First, the morphological component separation algorithm based on analytic dictionary is used to separate the components of SAR image. The structural component image with ship wake and the texture component image with speckle noise and sea clutter are obtained. Then, the local Radon transform is performed on the structural component that contains the ship wakes. Finally, the real and false local peak points are distinguished by the ship wake recognition algorithm based on peak clustering decision, so as to obtain the local peak points generated by the real wakes and determine the specific position of the ship wakes. The experimental results show that the proposed algorithm can effectively detect the ship wakes in SAR images.

Key words: synthetic aperture radar (SAR) image, ship wake, multiplicative noise denoising, sparse representation, Radon transform

中图分类号:

TP751

赵婷, 王申涛, 牛林, 席沛丽, 蔡云泽. 合成孔径雷达图像舰船尾迹检测算法[J]. 上海交通大学学报, 2020, 54(12): 1259-1268.

ZHAO Ting, WANG Shentao, NIU Lin, XI Peili, CAI Yunze. Detection Algorithm of Ship Wake in SAR Images[J]. Journal of Shanghai Jiao Tong University, 2020, 54(12): 1259-1268.

图/表 14

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参考文献 20

[1]	鲁自立，贾鑫，朱卫纲，等．SAR图像相干斑抑制方法综述[J].兵器装备工程学报，2017, 38(6): 104-108.
	LU Zili, JIA Xin, ZHU Weigang, et al. Study on SAR image despeckling algorithm[J]. Journal of Ordnance Equipment Engineering, 2017, 38(6): 104-108.
[2]	王宇航，范文义，张金虎. SAR图像滤波方法比较与分析[J].森林工程，2015, 31(3): 81-84.
	WANG Yuhang, FAN Wenyi, ZHANG Jinhu. The comparison and analysis of SAR image filtering methods[J]. Forest Engineering, 2015, 31(3): 81-84.
[3]	刘帅奇，扈琪，刘彤，等. 合成孔径雷达图像去噪算法研究综述[J].兵器装备工程学报，2018, 39(12): 106-112.
	LIU Shuaiqi, HU Qi, LIU Tong, et al. Review on synthetic aperture radar image denoising algorithms[J]. Journal of Ordnance Equipment Engineering, 2018, 39(12): 106-112.
[4]	LIU S, LIU M, LI P, et al. SAR image denoising via sparse representation in shearlet domain based on continuous cycle spinning[J]. IEEE Transactions on Geoscience and Remote Sensing, 2017, 55(5): 2985-2992.
[5]	DING Y, SELESNICK I W. Artifact-free wavelet denoising: Non-convex sparse regularization, convex optimization[J]. IEEE Signal Processing Letters, 2015, 22(9): 1364-1368.
[6]	TAN C, WEI Z H, WU Z B, et al. Parallel optimization of K-SVD algorithm for image denoising based on Spark[C]∥2016 IEEE 13th International Conference on Signal Processing (ICSP). Chengdu: IEEE, 2016: 820-825.
[7]	XU B, CUI Y, LI Z H, et al. An iterative SAR image filtering method using nonlocal sparse model[J]. IEEE Geoscience and Remote Sensing Letters, 2015, 12(8): 1635-1639.
[8]	SANG C W, SUN H. Two-step sparse decomposition for SAR image despeckling[J]. IEEE Geoscience and Remote Sensing Letters, 2017, 14(8): 1263-1267.
[9]	XU Z Z, SHIN B S, KLETTE R. Accurate and robust line segment extraction using minimum entropy with hough transform[J]. IEEE Transactions on Image Processing, 2015, 24(3): 813-822.
[10]	JAFARI-KHOUZANI K, SOLTANIAN-ZADEH H. Radon transform orientation estimation for rotation invariant texture analysis[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005, 27(6): 1004-1008.
[11]	AI J Q, QI X Y, YU W D, et al. A novel ship wake CFAR detection algorithm based on SCR enhancement and normalized Hough transform[J]. IEEE Geoscience and Remote Sensing Letters, 2011, 8(4): 681-685.
[12]	贾延明，张永涛. 基于Hough变换的舰船尾迹检测研究[J]. 舰船科学技术，2016, 38(4): 19-21.
	JIA Yanming, ZHANG Yongtao. Research on ship wake detection based on Hough transform[J]. Ship Science and Technology, 2016, 38(4): 19-21.
[13]	BIONDI F. Low-rank plus sparse decomposition and localized radon transform for ship-wake detection in synthetic aperture radar images[J]. IEEE Geoscience and Remote Sensing Letters, 2018, 15(1): 117-121.
[14]	江源，李健伟. 基于局部脊波变换的SAR图像舰船尾迹检测方法[J]. 舰船科学技术，2015, 37(11): 146-150.
	JIANG Yuan, LI Jianwei. A method of ship wake detection in SAR imagery based on localized ridgelet transform[J]. Ship Science and Technology, 2015, 37(11): 146-150.
[15]	牛林. SAR图像相干斑抑制及舰船尾迹检测方法研究[D]. 上海：上海交通大学，2019.
	NIU Lin. SAR Image despeckling and ship wake detection methods[D]. Shanghai: Shanghai Jiao Tong University, 2019.
[16]	杨国铮，禹晶，肖创柏，等. 基于形态字典学习的复杂背景SAR图像舰船尾迹检测[J]. 自动化学报，2017, 43(10): 1713-1725.
	YANG Guozheng, YU Jing, XIAO Chuangbai, et al. Ship wake detection in SAR images with complex background using morphological dictionary learning[J]. Acta Automatica Sinica, 2017, 43(10): 1713-1725.
[17]	WEI L H, BALZ T, ZHANG L, et al. A novel fast approach for SAR tomography: Two-step iterative shrinkage/thresholding[J]. IEEE Geoscience and Remote Sensing Letters, 2015, 12(6): 1377-1381.
[18]	WAKIN M B. Sparse image and signal processing: Wavelets, curvelets, morphological diversity(Starck, J．- L．，et al；2010) [Book Reviews] [J]. IEEE Signal Processing Magazine, 2011, 28(5): 144-146.
[19]	邹焕新，匡纲要，郁文贤，等. 基于特征空间决策的SAR图像舰船尾迹检测算法[J]. 系统工程与电子技术，2004, 26(6): 726-730.
	ZOU Huanxin, KUANG Gangyao, YU Wenxian, et al. Detection algorithm of ship wakes from SAR image based on feature space decision[J]. Systems Engineering and Electronics, 2004, 26(6): 726-730.
[20]	ZHENG Y, FAN R L, QIU C L, et al. An improved algorithm for peak detection in mass spectra based on continuous wavelet transform[J]. International Journal of Mass Spectrometry, 2016, 409: 53-58.

评价指标	表达式	指标效果
边缘保持指数EPI		越接近1边缘保持程度越好
等效视数ENL		越大去噪效果越强
相干斑抑制因素F		越大去噪效果越强，原图为1
相干斑指数β		越小相干斑强度小，噪声去除效果越好
均值保持指数PM		越接近1均值保持效果越好

图像	EPI		ENL		F		β		PM
图像	原图	滤波后结构成分图	原图	滤波后结构成分图	原图	滤波后结构成分图	原图	滤波后结构成分图	原图	滤波后结构成分图
图5(a)	—	0.16	2.01	22.5	—	1.30	0.70	0.62	—	1.00
图5(b)	—	0.20	2.49	10.2	—	4.41	0.63	0.31	—	0.97
图5(c)	—	0.20	3.12	23.0	—	7.87	0.57	0.21	—	0.97
图5(d)	—	0.18	21.5	113.0	—	5.31	0.22	0.09	—	0.99
图5(e)	—	0.02	2.10	31.4	—	15.9	0.69	0.18	—	0.97
图5(f)	—	0.20	3.55	26.0	—	7.87	0.53	0.20	—	0.96

算法	EPI	ENL	F	β	PM
原图	—	2.01	—	0.70	—
Lee滤波	0.24	10.20	5.10	0.31	0.99
增强Lee滤波	0.50	3.67	2.63	0.52	0.83
双边滤波	0.26	10.10	5.12	0.35	0.99
Kuan滤波	0.41	7.25	3.58	0.37	1.00
本文算法	0.16	22.50	11.90	0.21	0.97

m	G_m	H_m	D_m
1	0.405	0.170	0.264
2	1.000	1.000	1.000

合成孔径雷达图像舰船尾迹检测算法

Detection Algorithm of Ship Wake in SAR Images

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