Compressive sampling in passive millimeter-wave imaging

N. Gopalsami*, T. W. Elmer, S. Liao, R. Ahern, A. Heifetz, A. C. Raptis, M. Luessi, D. Babacan, Aggelos K Katsaggelos

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Scopus citations

Abstract

We present a Hadamard transform based imaging technique and have implemented it on a single-pixel passive millimeter-wave imager in the 146-154 GHz range. The imaging arrangement uses a set of Hadamard transform masks of size p × q at the image plane of a lens and the transformed image signals are focused and collected by a horn antenna of the imager. The cyclic nature of Hadamard matrix allows the use of a single extended 2-D Hadamard mask of size (2p-1) × (2q-1) to expose a p × q submask for each acquisition by raster scanning the large mask one pixel at a time. A total of N = pq acquisitions can be made with a complete scan. The original p × q image may be reconstructed by a simple matrix operation. Instead of full N acquisitions, we can use a subset of the masks for compressive sensing. In this regard, we have developed a relaxation technique that recovers the full Hadamard measurement space from subsampled Hadamard acquisitions. We have reconstructed high fidelity images with 1/9 of the full Hadamard acquisitions, thus reducing the image acquisition time by a factor of 9.

Original languageEnglish (US)
Title of host publicationPassive Millimeter-Wave Imaging Technology XIV
DOIs
StatePublished - 2011
EventPassive Millimeter-Wave Imaging Technology XIV - Orlando, FL, United States
Duration: Apr 28 2011Apr 28 2011

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume8022
ISSN (Print)0277-786X

Other

OtherPassive Millimeter-Wave Imaging Technology XIV
Country/TerritoryUnited States
CityOrlando, FL
Period4/28/114/28/11

Keywords

  • Compressive sensing
  • Hadamard transform
  • Millimeter wave
  • Passive

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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