PMO OpenIR
Millimeter-Wave InSAR Image Reconstruction Approach by Total Variation Regularized Matrix Completion
Zhang, Yilong1,2; Miao, Wei1,2; Lin, Zhenhui1,2; Gao, Hao1,2; Shi, Shengcai1,2
2018-07-01
Source PublicationREMOTE SENSING
ISSN2072-4292
Volume10Issue:7Pages:16
Abstract

Millimeter-wave interferometric synthetic aperture radiometer (InSAR) can provide high-resolution observations for many applications by using small antennas to achieve very large synthetic aperture. However, reconstruction of a millimeter-wave InSAR image has been proven to be an ill-posed inverse problem that degrades the performance of InSAR imaging. In this paper, a novel millimeter-wave InSAR image reconstruction approach, referred to as InSAR-TVMC, by total variation (TV) regularized matrix completion (MC) in two-dimensional data space, is proposed. Based on the a priori knowledge that natural millimeter-wave images statistically hold the low-rank property, the proposed approach represents the object images as low-rank matrices and formulates the data acquisition of InSAR in two-dimensional data space directly to undersample visibility function samples. Subsequently, using the undersampled visibility function samples, the optimal solution of the InSAR image reconstruction problem is obtained by simultaneously adopting MC techniques and TV regularization. Experimental results on simulated and real millimeter-wave InSAR image data demonstrate the effectiveness and the significant improvement of the reconstruction performance of the proposed InSAR-TVMC approach over conventional and one-dimensional sparse InSAR image reconstruction approaches.

Keywordmillimeter-wave interferometric synthetic aperture radiometer image reconstruction total variation matrix completion undersampling
DOI10.3390/rs10071053
WOS KeywordTOTAL-VARIATION MINIMIZATION ; THRESHOLDING ALGORITHM ; NEAR-FIELD ; APERTURE ; RADIOMETRY ; RANK
Indexed BySCI
Language英语
WOS Research AreaRemote Sensing
WOS SubjectRemote Sensing
WOS IDWOS:000440332500076
PublisherMDPI
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://libir.pmo.ac.cn/handle/332002/21585
Collection中国科学院紫金山天文台
Corresponding AuthorZhang, Yilong
Affiliation1.Chinese Acad Sci, Purple Mt Observ, Nanjing 210034, Jiangsu, Peoples R China
2.Chinese Acad Sci, Key Lab Radio Astron, Nanjing 210034, Jiangsu, Peoples R China
Recommended Citation
GB/T 7714
Zhang, Yilong,Miao, Wei,Lin, Zhenhui,et al. Millimeter-Wave InSAR Image Reconstruction Approach by Total Variation Regularized Matrix Completion[J]. REMOTE SENSING,2018,10(7):16.
APA Zhang, Yilong,Miao, Wei,Lin, Zhenhui,Gao, Hao,&Shi, Shengcai.(2018).Millimeter-Wave InSAR Image Reconstruction Approach by Total Variation Regularized Matrix Completion.REMOTE SENSING,10(7),16.
MLA Zhang, Yilong,et al."Millimeter-Wave InSAR Image Reconstruction Approach by Total Variation Regularized Matrix Completion".REMOTE SENSING 10.7(2018):16.
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