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Proceedings Paper

Exploiting k-space/frequency duality in Fourier optics toward real-time compression-less terahertz imaging
Author(s): Hichem Guerboukha; Kathirvel Nallappan; Maksim Skorobogatiy
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Paper Abstract

We present a theoretical formulation and an experimental demonstration of a fast compression-less terahertz imaging technique based on broadband Fourier optics. The technique exploits k-vector/frequency duality in Fourier optics which allows to use a single-pixel detector to perform angular scan along a circular path, while the broadband spectrum is used to scan along the radial dimension in Fourier domain. The proposed compression-less image reconstruction technique (hybrid inverse transform) requires only a small number of measurements that scales linearly with the image linear size, thus promising real-time acquisition of high-resolution THz images. We develop an algorithm based on a polar formulation of the Fourier transform to reconstruct the image. First, we show how the equations are transformed when passing from a spatial integral to a frequency integral. Second, we analytically demonstrate that, in the case of binary amplitude objects and phase objects, the reconstructed image from our formulation is proportional to the original object. Third, we experimentally demonstrate the image reconstruction method in the two above-mentioned cases: we use a metal aperture for the binary object and an engraving in a polymer sample for the phase object. A detailed analysis of the novel technique advantages and limitations is presented, and its place among other existing THz imaging techniques is clearly identified.

Paper Details

Date Published: 14 May 2018
PDF: 7 pages
Proc. SPIE 10669, Computational Imaging III, 106690N (14 May 2018); doi: 10.1117/12.2304892
Show Author Affiliations
Hichem Guerboukha, Ecole Polytechnique de Montréal (Canada)
Kathirvel Nallappan, Ecole Polytechnique de Montréal (Canada)
Maksim Skorobogatiy, Ecole Polytechnique de Montréal (Canada)

Published in SPIE Proceedings Vol. 10669:
Computational Imaging III
Abhijit Mahalanobis; Amit Ashok; Lei Tian; Jonathan C. Petruccelli, Editor(s)

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