Incorporating Spatial Priors in Microwave Imaging via Multiplicative Regularization

被引：11
作者：
Bayat, Nozhan [1 ]
Mojabi, Puyan [1 ]
机构：
[1] Univ Manitoba, Dept Elect & Comp Engn, Winnipeg, MB R3T 2N2, Canada
来源：
IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION | 2020年 / 68卷 / 02期
基金：
加拿大自然科学与工程研究理事会;
关键词：
Permittivity; Image reconstruction; Microwave imaging; Antennas; Microwave FET integrated circuits; Microwave integrated circuits; Inverse scattering; microwave imaging (MWI); regularization; spatial priors (SP); REALISTIC NUMERICAL BREAST; DIELECTRIC-PROPERTIES; INVERSION METHOD; PHANTOMS; CANCER;
D O I：
10.1109/TAP.2019.2943329
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This article presents a microwave imaging (MWI) algorithm that can incorporate prior structural information, also known as spatial priors (SP), about the object being imaged to enhance the achievable image quantitative accuracy. This algorithm: 1) is fully automated and 2) can work with both complete and partially available structural information. The core idea of this imaging algorithm is to use a multiplicative regularization term to incorporate SP, and a second regularization term to handle the lack of structural information in a given part of the imaging domain. This algorithm, which has been implemented for the 2-D transverse magnetic case, is evaluated against single-frequency and multiple-frequency synthetic and experimental MWI data sets.
引用
收藏
页码：1107 / 1118
页数：12
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