Compressive passive millimeter-wave imaging

S. D. Babacan*, M. Luessi, L. Spinoulas, A. K. Katsaggelos, N. Gopalsami, T. Elmer, R. Ahern, S. Liao, A. Raptis

*Corresponding author for this work

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

37 Scopus citations


In this paper, we present a novel passive millimeter-wave (PMMW) imaging system designed using compressive sensing principles. We employ randomly encoded masks at the focal plane of the PMMW imager to acquire incoherent measurements of the imaged scene. We develop a Bayesian reconstruction algorithm to estimate the original image from these measurements, where the sparsity inherent to typical PMMW images is efficiently exploited. Comparisons with other existing reconstruction methods show that the proposed reconstruction algorithm provides higher quality image estimates. Finally, we demonstrate with simulations using real PMMW images that the imaging duration can be dramatically reduced by acquiring only a few measurements compared to the size of the image.

Original languageEnglish (US)
Title of host publicationICIP 2011
Subtitle of host publication2011 18th IEEE International Conference on Image Processing
Number of pages4
StatePublished - Dec 1 2011
Event2011 18th IEEE International Conference on Image Processing, ICIP 2011 - Brussels, Belgium
Duration: Sep 11 2011Sep 14 2011

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880


Other2011 18th IEEE International Conference on Image Processing, ICIP 2011


  • Bayesian methods
  • Passive millimeter wave imaging
  • compressive sensing
  • sparse reconstruction

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing


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