Compressive Sensing Holographic Microwave Random Array Imaging of Dielectric Inclusion
Holographic microwave imaging is an innovative method to image biological objects based on their dielectric properties, which has the advantages of high spatial resolution. However, the image reconstruction method is always a critical issue in holographic microwave imaging. This research aims to inv...
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doaj-e5ac7d9f67b94e1ba66e4ae8b7dcfc152021-03-29T20:56:23ZengIEEEIEEE Access2169-35362018-01-016564775648710.1109/ACCESS.2018.28727608478248Compressive Sensing Holographic Microwave Random Array Imaging of Dielectric InclusionLulu Wang0https://orcid.org/0000-0001-7466-9522Mostafa Fatemi1School of Instrument Science and Opto-electronics Engineering, Hefei University of Technology, Hefei, ChinaDepartment of Physiology and Biophysics, Mayo Clinic and Mayo Foundation, Rochester, MN, USAHolographic microwave imaging is an innovative method to image biological objects based on their dielectric properties, which has the advantages of high spatial resolution. However, the image reconstruction method is always a critical issue in holographic microwave imaging. This research aims to investigate the feasibility and effectiveness of applying compressive sensing (CS) technique to the holographic microwave imaging for small dielectric object detection. This paper presents a compressive sensing holographic microwave random array imaging (CS-HMRAI) method for imaging of dielectric objects. A numerical system consists of various dielectric models and imaging processing model are developed to evaluate the proposed approach. The split Bregman (SB) and orthogonal matching pursuit (OMP) algorithms are applied to HMRAI for evaluation of small inclusions embedded in dielectric objects. Various experiments are conducted to identify lesions using the proposed CS-HMRAI method and results are compared with HMRAI and HMRAI via OMP methods. Both simulation and experimental results demonstrate that CS-HMRAI via SB can produce high-quality images and detect arbitrarily shaped small inclusions with random sizes and locations by using significantly fewer sensors and scanning times than the HMRAI and CS-HMRAI via OMP approaches. The proposed approach has the potential for further investigation for breast tumor detection in a fast and cost-effective manner.https://ieeexplore.ieee.org/document/8478248/Microwave imagingholographic microwave imagingcompressive sensingsplit Bregmanorthogonal matching pursuit |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Lulu Wang Mostafa Fatemi |
spellingShingle |
Lulu Wang Mostafa Fatemi Compressive Sensing Holographic Microwave Random Array Imaging of Dielectric Inclusion IEEE Access Microwave imaging holographic microwave imaging compressive sensing split Bregman orthogonal matching pursuit |
author_facet |
Lulu Wang Mostafa Fatemi |
author_sort |
Lulu Wang |
title |
Compressive Sensing Holographic Microwave Random Array Imaging of Dielectric Inclusion |
title_short |
Compressive Sensing Holographic Microwave Random Array Imaging of Dielectric Inclusion |
title_full |
Compressive Sensing Holographic Microwave Random Array Imaging of Dielectric Inclusion |
title_fullStr |
Compressive Sensing Holographic Microwave Random Array Imaging of Dielectric Inclusion |
title_full_unstemmed |
Compressive Sensing Holographic Microwave Random Array Imaging of Dielectric Inclusion |
title_sort |
compressive sensing holographic microwave random array imaging of dielectric inclusion |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2018-01-01 |
description |
Holographic microwave imaging is an innovative method to image biological objects based on their dielectric properties, which has the advantages of high spatial resolution. However, the image reconstruction method is always a critical issue in holographic microwave imaging. This research aims to investigate the feasibility and effectiveness of applying compressive sensing (CS) technique to the holographic microwave imaging for small dielectric object detection. This paper presents a compressive sensing holographic microwave random array imaging (CS-HMRAI) method for imaging of dielectric objects. A numerical system consists of various dielectric models and imaging processing model are developed to evaluate the proposed approach. The split Bregman (SB) and orthogonal matching pursuit (OMP) algorithms are applied to HMRAI for evaluation of small inclusions embedded in dielectric objects. Various experiments are conducted to identify lesions using the proposed CS-HMRAI method and results are compared with HMRAI and HMRAI via OMP methods. Both simulation and experimental results demonstrate that CS-HMRAI via SB can produce high-quality images and detect arbitrarily shaped small inclusions with random sizes and locations by using significantly fewer sensors and scanning times than the HMRAI and CS-HMRAI via OMP approaches. The proposed approach has the potential for further investigation for breast tumor detection in a fast and cost-effective manner. |
topic |
Microwave imaging holographic microwave imaging compressive sensing split Bregman orthogonal matching pursuit |
url |
https://ieeexplore.ieee.org/document/8478248/ |
work_keys_str_mv |
AT luluwang compressivesensingholographicmicrowaverandomarrayimagingofdielectricinclusion AT mostafafatemi compressivesensingholographicmicrowaverandomarrayimagingofdielectricinclusion |
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1724193888382484480 |