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Experimental demonstration of object identification by analyzing 2-dimensional complex spectra of Laguerre-Gaussian modes (Conference Presentation)
Author(s): Jing Du; Zhe Zhao; Runzhou Zhang; Guodong Xie; Long Li; Haoqian Song; Kai Pang; Cong Liu; Hao Song; Ahmed Almaiman; Shlomo Zach; Nadav Cohen; Moshe Tur; Alan E. Willner

Paper Abstract

We recover the shape and orientation of an object by analyzing the spatial phase and amplitude of a transmitted optical beam using a single pixel. We experimentally demonstrate using the complex spatial spectrum of multiple sequential measurements of a varying probe beam. Specifically, we transmit a structured beam that is tailored to have one mode of the Laguerre-Gaussian (LG) modal basis set, and the beam is varied to sequentially have a unique azimuthal (l) and radial (p) value. When each uniquely structured beam probes an object, there will be coupling of power from the pure mode to other LG modes. The complex phase and amplitude coefficients of this modal power coupling will provide a “signature” of the probed object’s 2D structure, and this signature can be detected using a single pixel. We identify a “fan-shaped” object with an opening angle of 120˚ and different angular orientations by analyzing the corresponding complex spatial spectrum of multiple sequential measurements, such that each subsequent tailored mode has l and p indices in the range -15 - +15 and 0-30, respectively. Results show that the amplitude spectrum is insensitive to the object’s angular orientation, whereas the phase spectrum predictably shifts with orientation. Additionally, we demonstrate that an irregular image with a ‘SC’ logo can be reconstructed using the complex modal spectrum. The structural similarity (SSIM) of the reconstructed image increases as the number of modes increases. Specifically, the SSIM increases by 83.5% when the number of modes increases from 36 (6 by 6) to 961 (31 by 31).

Paper Details

Date Published: 10 September 2019
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Proc. SPIE 11135, Unconventional and Indirect Imaging, Image Reconstruction, and Wavefront Sensing 2019, 111350K (10 September 2019); doi: 10.1117/12.2531401
Show Author Affiliations
Jing Du, The Univ. of Southern California (United States)
Zhe Zhao, The Univ. of Southern California (United States)
Runzhou Zhang, The Univ. of Southern California (United States)
Guodong Xie, The Univ. of Southern California (United States)
Long Li, The Univ. of Southern California (United States)
Haoqian Song, The Univ. of Southern California (United States)
Kai Pang, The Univ. of Southern California (United States)
Cong Liu, The Univ. of Southern California (United States)
Hao Song, The Univ. of Southern California (United States)
Ahmed Almaiman, The Univ. of Southern California (United States)
Shlomo Zach, Tel Aviv Univ. (Israel)
Nadav Cohen, Tel Aviv Univ. (Israel)
Moshe Tur, Tel Aviv Univ. (Israel)
Alan E. Willner, The Univ. of Southern California (United States)


Published in SPIE Proceedings Vol. 11135:
Unconventional and Indirect Imaging, Image Reconstruction, and Wavefront Sensing 2019
Jean J. Dolne; Mark F. Spencer; Markus E. Testorf, Editor(s)

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