A new nonlocal TV-based variational model for SAR image despeckling based on the G(0) distribution

doi:10.1016/j.dsp.2017.05.008

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 互联网大数据与信息安全

	A new nonlocal TV-based variational model for SAR image despeckling based on the G(0) distribution
	Nie, Xiangli1 ; Huang, Xiayuan1 ; Feng, Wensen 2
发表期刊	DIGITAL SIGNAL PROCESSING
	2017-09-01
卷号	68 期号:68 页码:44-56
文章类型	Article
摘要	In 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.
关键词	Synthetic Aperture Radar (Sar) Speckle Noise g(0) Distribution Nonlocal Total Variation (Nltv) Primal-dual Algorithm Mellin Transform (Mt)
WOS标题词	Science & Technology ; Technology
DOI	10.1016/j.dsp.2017.05.008
关键词[WOS]	MULTIPLICATIVE NOISE ; SPECKLE REDUCTION ; WAVELET DOMAIN ; STATISTICS ; CLUTTER ; FILTER ; MARKOV
收录类别	SCI
所属项目编号	61602483
语种	英语
项目资助者	National Natural Science Foundation of China(61602483 ; Beijing Natural Science Foundation(4174107) ; Early Career Development Award of SKLMCCS(Y659011F4A) ; 61379093 ; 91648205)
WOS研究方向	Engineering
WOS类目	Engineering, Electrical & Electronic
WOS记录号	WOS:000407409100005
引用统计	被引频次：11[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/173211/19385
专题	多模态人工智能系统全国重点实验室_互联网大数据与信息安全复杂系统管理与控制国家重点实验室
通讯作者	Nie, Xiangli
作者单位	1.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
第一作者单位	中国科学院自动化研究所
通讯作者单位	中国科学院自动化研究所
推荐引用方式 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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