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Photonic Sensors

, Volume 9, Issue 2, pp 115–125 | Cite as

Surface Measurement Using Compressed Wavefront Sensing

  • Eddy Mun Tik Chow
  • Ningqun Guo
  • Edwin Chong
  • Xin WangEmail author
Open Access
Regular
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Abstract

Compressed sensing leverages the sparsity of signals to reduce the amount of measurements required for its reconstruction. The Shack-Hartmann wavefront sensor meanwhile is a flexible sensor where its sensitivity and dynamic range can be adjusted based on applications. An investigation is done by using compressed sensing in surface measurements with the Shack-Hartmann wavefront sensor. The results show that compressed sensing paired with the Shack-Hartmann wavefront sensor can reliably measure surfaces accurately. The performance of compressed sensing is compared with those of the iterative modal-based wavefront reconstruction and Fourier demodulation of Shack-Hartmann spot images. Compressed sensing performs comparably to the modal based iterative wavefront reconstruction in both simulation and experiment while performing better than the Fourier demodulation in simulation.

Keywords

Shack-Hartmann wavefront sensor surface measurement compressed sensing 

Notes

Acknowledgement

The authors gratefully acknowledge the support of funding from Ministry of Higher Education, Malaysia under the Grant No. FRGS/1/2016/STG02/MUSM/02/1.

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Copyright information

© The Author(s) 2018

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (https://doi.org/creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  • Eddy Mun Tik Chow
    • 1
  • Ningqun Guo
    • 1
  • Edwin Chong
    • 2
  • Xin Wang
    • 1
    Email author
  1. 1.School of EngineeringMonash University Malaysia, Jalan Lagoon SelatanBandar SunwayMalaysia
  2. 2.Department of Electrical and Computer EngineeringColorado State UniversityFort CollinsUSA

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