Filtered Convolution for Synthetic Aperture Radar Images Ship Detection

doi:10.3390/rs14205257

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 先进时空数据分析与学习

	Filtered Convolution for Synthetic Aperture Radar Images Ship Detection
	Zhang, Luyang 1,2; Wang, Haitao1 ; Wang, Lingfeng3 ; Pan, Chunhong2 ; Huo, Chunlei2 ; Liu, Qiang 1; Wang, Xinyao 1
发表期刊	REMOTE SENSING
	2022-10-01
卷号	14 期号:20 页码:19
通讯作者	Wang, Haitao(htwang@nuaa.edu.cn)
摘要	Synthetic aperture radar (SAR) image ship detection is currently a research hotspot in the field of national defense science and technology. However, SAR images contain a large amount of coherent speckle noise, which poses significant challenges in the task of ship detection. To address this issue, we propose filter convolution, a novel design that replaces the traditional convolution layer and suppresses coherent speckle noise while extracting features. Specifically, the convolution kernel of the filter convolution comes from the input and is generated by two modules: the kernel-generation module and local weight generation module. The kernel-generation module is a dynamic structure that generates dynamic convolution kernels using input image or feature information. The local weight generation module is based on the statistical characteristics of the input images or features and is used to generate local weights. The introduction of local weights allows the extracted features to contain more local characteristic information, which is conducive to ship detection in SAR images. In addition, we proved that the fusion of the proposed kernel-generation module and the local weight module can suppress coherent speckle noise in the SAR image. The experimental results show the excellent performance of our method on a large-scale SAR ship detection dataset-v1.0 (LS-SSDD-v1.0). It also achieved state-of-the-art performance on a high-resolution SAR image dataset (HRSID), which confirmed its applicability.
关键词	synthetic aperture radar (SAR) remote sensing image ship detection filter convolution coherent speckle noise local weight
DOI	10.3390/rs14205257
关键词[WOS]	SPECKLE ; NOISE
收录类别	SCI
语种	英语
资助项目	Nondestructive Detection and Monitoring Technology for High Speed Transportation Facilities ; Key Laboratory of Ministry of Industry and Information Technology ; Fundamental Research Funds for the Central Universities[NJ2020014] ; Fund of Fundamental Research Funds for the Central Universities[buctrc202221]
项目资助者	Nondestructive Detection and Monitoring Technology for High Speed Transportation Facilities ; Key Laboratory of Ministry of Industry and Information Technology ; Fundamental Research Funds for the Central Universities ; Fund of Fundamental Research Funds for the Central Universities
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS记录号	WOS:000873506900001
出版者	MDPI
引用统计	被引频次：3[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/50484
专题	多模态人工智能系统全国重点实验室_先进时空数据分析与学习
通讯作者	Wang, Haitao
作者单位	1.Nanjing Univ Aeronaut & Astronaut, Coll Automat Engn, Nanjing 210016, Peoples R China 2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China 3.Beijing Univ Chem Technol, Coll Informat Sci & Technol, Beijing 100029, Peoples R China
第一作者单位	模式识别国家重点实验室
推荐引用方式 GB/T 7714	Zhang, Luyang,Wang, Haitao,Wang, Lingfeng,et al. Filtered Convolution for Synthetic Aperture Radar Images Ship Detection[J]. REMOTE SENSING,2022,14(20):19.
APA	Zhang, Luyang.,Wang, Haitao.,Wang, Lingfeng.,Pan, Chunhong.,Huo, Chunlei.,...&Wang, Xinyao.(2022).Filtered Convolution for Synthetic Aperture Radar Images Ship Detection.REMOTE SENSING,14(20),19.
MLA	Zhang, Luyang,et al."Filtered Convolution for Synthetic Aperture Radar Images Ship Detection".REMOTE SENSING 14.20(2022):19.