A new nonlocal TV-based variational model for SAR image despeckling based on the G(0) distribution
Nie, Xiangli1; Huang, Xiayuan1; Feng, Wensen2
Source PublicationDIGITAL SIGNAL PROCESSING
2017-09-01
Volume68Issue:68Pages:44-56
SubtypeArticle
AbstractIn this paper, we propose a new variational model for speckle reduction of synthetic aperture radar (SAR) images based on the G(0) statistical distribution and nonlocal total variation (NLTV) regularization. The existing variational models for SAR despeckling regard the terrain backscatters as nonrandom, which is only suitable to depict the homogeneous regions. For inhomogeneous scenes, the backscatter fluctuations should be taken into account. Motivated by this, the inverse Gamma distribution is used to model the statistical property of the underlying terrain backscatter. By using the maximum a posteriori rule and NLTV penalty, a new variational model, named G(0) NLTV, is derived. The parameters in the model are estimated based on the Mellin transform of the G(0) distributions according to the local heterogeneity. Since this model lacks the global convexity, a convex model is obtained by utilizing the logarithm transformation and variable substitution. Then, the primal-dual algorithm is used to solve this optimization problem. Experimental results on both synthetic and real SAR images demonstrate the effectiveness of the proposed method. (C) 2017 Elsevier Inc. All rights reserved.
KeywordSynthetic Aperture Radar (Sar) Speckle Noise g(0) Distribution Nonlocal Total Variation (Nltv) Primal-dual Algorithm Mellin Transform (Mt)
WOS HeadingsScience & Technology ; Technology
DOI10.1016/j.dsp.2017.05.008
WOS KeywordMULTIPLICATIVE NOISE ; SPECKLE REDUCTION ; WAVELET DOMAIN ; STATISTICS ; CLUTTER ; FILTER ; MARKOV
Indexed BySCI
Project Number61602483
Language英语
Funding OrganizationNational Natural Science Foundation of China(61602483 ; Beijing Natural Science Foundation(4174107) ; Early Career Development Award of SKLMCCS(Y659011F4A) ; 61379093 ; 91648205)
WOS Research AreaEngineering
WOS SubjectEngineering, Electrical & Electronic
WOS IDWOS:000407409100005
Citation statistics
Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/19385
Collection复杂系统管理与控制国家重点实验室_互联网大数据与信息安全
Corresponding AuthorNie, Xiangli
Affiliation1.Chinese Acad Sci, State Key Lab Management & Control Complex Syst, Inst Automat, Beijing 100190, Peoples R China
2.Huawei Technol Co Ltd, Medium Engn Dept, Cent Hardware Engn Inst, 2012 Labs, Shenzhen 518129, Peoples R China
Recommended Citation
GB/T 7714
Nie, Xiangli,Huang, Xiayuan,Feng, Wensen. A new nonlocal TV-based variational model for SAR image despeckling based on the G(0) distribution[J]. DIGITAL SIGNAL PROCESSING,2017,68(68):44-56.
APA Nie, Xiangli,Huang, Xiayuan,&Feng, Wensen.(2017).A new nonlocal TV-based variational model for SAR image despeckling based on the G(0) distribution.DIGITAL SIGNAL PROCESSING,68(68),44-56.
MLA Nie, Xiangli,et al."A new nonlocal TV-based variational model for SAR image despeckling based on the G(0) distribution".DIGITAL SIGNAL PROCESSING 68.68(2017):44-56.
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