Compressive Sensing Holographic Microwave Random Array Imaging of Dielectric Inclusion

Lulu Wang, Mostafa Fatemi

Research output: Contribution to journalArticle

3 Scopus citations

Abstract

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.

Original languageEnglish (US)
JournalIEEE Access
DOIs
StateAccepted/In press - Jan 1 2018

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Keywords

  • compressive sensing
  • holographic microwave imaging
  • microwave imaging
  • orthogonal matching pursuit
  • split Bregman

ASJC Scopus subject areas

  • Computer Science(all)
  • Materials Science(all)
  • Engineering(all)

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