SAR-to-Optical Image Translation With Hierarchical Latent Features

doi:10.1109/TGRS.2022.3200996

CORC > 自动化研究所 > 中国科学院自动化研究所 > 模式识别国家重点实验室 > 机器人视觉团队

	SAR-to-Optical Image Translation With Hierarchical Latent Features
	Wang, Haixia 1,2; Zhang, Zhigang 1,2; Hu, Zhanyi 3,4,5; Dong, Qiulei 3,4,5
刊名	IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
	2022
卷号	60 页码:12
关键词	Optical imaging Optical sensors Image reconstruction Radar polarimetry Adaptive optics Optical design Synthetic aperture radar Parallel generative adversarial model SAR synthetic aperture radar (SAR)-to-optical image translation
ISSN号	0196-2892
DOI	10.1109/TGRS.2022.3200996
通讯作者	Dong, Qiulei(qldong@nlpr.ia.ac.cn)
英文摘要	Due to the all-weather and all-time imaging capability of synthetic aperture radar (SAR), SAR remote sensing analysis has attracted much attention recently. However, compared with the optical images, SAR images are more difficult to be interpreted. If an SAR image could be translated into its corresponding optical image, then the generated optical image would be helpful for assisting the interpretation. Addressing this issue, we investigate how to translate SAR images into optical ones in this work and propose a parallel generative adversarial model for SAR-to-optical image translation, called parallel generative adversarial network (Parallel-GAN), consisting of a backbone image translation subnetwork and an adjoint optical image reconstruction subnetwork. Under the proposed model, the backbone image translation subnetwork is designed to translate SAR images into optical ones, and simultaneously some of its intermediate layers are required to output similar latent features to those from the corresponding layers of the adjoint image reconstruction subnetwork. Thanks to the imposed hierarchical latent optical features, the proposed Parallel-GAN could achieve the SAR-to-optical image translation effectively. Extensive experimental results on three public datasets demonstrate that the proposed method outperforms ten state-of-the-art methods for SAR-to-optical image translation.
资助项目	National Natural Science Foundation of China[61991423] ; National Natural Science Foundation of China[U1805264] ; National Natural Science Foundation of China[62073199] ; National Natural Science Foundation of China[61773245] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDB32050100] ; Natural Science Foundation of Shandong Province[ZR2020MF095] ; Science and Technology Project of Qingdao West Coast New Area[2021-6] ; Beijing Municipal Science and Technology Project[Z211100011021004]
WOS关键词	NETWORK
WOS研究方向	Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000852237000008
资助机构	National Natural Science Foundation of China ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Natural Science Foundation of Shandong Province ; Science and Technology Project of Qingdao West Coast New Area ; Beijing Municipal Science and Technology Project
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/50077]
专题	自动化研究所_模式识别国家重点实验室_机器人视觉团队
通讯作者	Dong, Qiulei
作者单位	1.Shandong Univ Sci & Technol, Coll Elect Engn & Automat, Qingdao 266590, Peoples R China 2.Shandong Univ Sci & Technol, Key Lab Robot & Intelligent Technol Shandong Prov, Qingdao 266590, Peoples R China 3.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China 4.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Beijing 100190, Peoples R China 5.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Wang, Haixia,Zhang, Zhigang,Hu, Zhanyi,et al. SAR-to-Optical Image Translation With Hierarchical Latent Features[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2022,60:12.
APA	Wang, Haixia,Zhang, Zhigang,Hu, Zhanyi,&Dong, Qiulei.(2022).SAR-to-Optical Image Translation With Hierarchical Latent Features.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,60,12.
MLA	Wang, Haixia,et al."SAR-to-Optical Image Translation With Hierarchical Latent Features".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 60(2022):12.