Millimeter-wave compressive holography.
Abstract
We describe an active millimeter-wave holographic imaging system that uses compressive
measurements for three-dimensional (3D) tomographic object estimation. Our system
records a two-dimensional (2D) digitized Gabor hologram by translating a single pixel
incoherent receiver. Two approaches for compressive measurement are undertaken: nonlinear
inversion of a 2D Gabor hologram for 3D object estimation and nonlinear inversion
of a randomly subsampled Gabor hologram for 3D object estimation. The object estimation
algorithm minimizes a convex quadratic problem using total variation (TV) regularization
for 3D object estimation. We compare object reconstructions using linear backpropagation
and TV minimization, and we present simulated and experimental reconstructions from
both compressive measurement strategies. In contrast with backpropagation, which estimates
the 3D electromagnetic field, TV minimization estimates the 3D object that produces
the field. Despite undersampling, range resolution is consistent with the extent of
the 3D object band volume.
Type
Journal articlePermalink
https://hdl.handle.net/10161/4205Collections
More Info
Show full item recordScholars@Duke
David J. Brady
Michael J. Fitzpatrick Distinguished Professor Emeritus of Photonics
David Brady leads the Duke Information Spaces Project (DISP). Historically, DISP has
focused on computational imaging systems, with particular emphasis on smart cameras
for security, consumer, transportation and broadcast applications. Currently DISP
focuses primarily on the use of artificial intelligence in camera arrays for interactive
broadcasting.

Articles written by Duke faculty are made available through the campus open access policy. For more information see: Duke Open Access Policy
Rights for Collection: Scholarly Articles
Works are deposited here by their authors, and represent their research and opinions, not that of Duke University. Some materials and descriptions may include offensive content. More info