A Bayesian-Compressive-Sampling-Based Inversion for Imaging Sparse Scatterers

被引：160
作者：
Oliveri, Giacomo [1 ]
Rocca, Paolo [1 ]
Massa, Andrea [1 ]
机构：
[1] Univ Trento, ELEDIA Res Grp, Dept Informat Engn & Comp Sci, I-38050 Trento, Italy
来源：
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING | 2011年 / 49卷 / 10期
关键词：
Bayesian compressive sampling (BCS); contrast source formulation; inverse scattering; microwave imaging; relevance vector machine (RVM); IMPLEMENTATION;
D O I：
10.1109/TGRS.2011.2128329
中图分类号：
P3 [地球物理学]; P59 [地球化学];
学科分类号：
0708 ; 070902 ;
摘要：
In this paper, a new approach based on the Bayesian compressive sampling (BCS) and within the contrast source formulation of an inverse scattering problem is proposed for imaging sparse scatterers. By enforcing a probabilistic hierarchical prior as a sparsity regularization constraint, the problem is solved by means of a fast relevance vector machine. The effectiveness and robustness of the BCS-based approach are assessed through a set of numerical experiments concerned with various scatterer configurations and different noisy conditions.
引用
收藏
页码：3993 / 4006
页数：14
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