Detection Algorithm of Ship Wake in SAR Images

doi:10.16183/j.cnki.jsjtu.2019.311

Abstract

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

CLC Number:

TP751

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.

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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