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

页码：3993 / 4006

页数：14

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