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Optics Letters

Optics Letters


  • Editor: Xi-Cheng Zhang
  • Vol. 39, Iss. 5 — Mar. 1, 2014
  • pp: 1189–1192

Compressed wavefront sensing

James Polans, Ryan P. McNabb, Joseph A. Izatt, and Sina Farsiu  »View Author Affiliations

Optics Letters, Vol. 39, Issue 5, pp. 1189-1192 (2014)

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We report on an algorithm for fast wavefront sensing that incorporates sparse representation for the first time in practice. The partial derivatives of optical wavefronts were sampled sparsely with a Shack–Hartmann wavefront sensor (SHWFS) by randomly subsampling the original SHWFS data to as little as 5%. Reconstruction was performed by a sparse representation algorithm that utilized the Zernike basis. We name this method sparse Zernike (SPARZER). Experiments on real and simulated data attest to the accuracy of the proposed techniques as compared to traditional sampling and reconstruction methods. We have made the corresponding dataset and software freely available online. Compressed wavefront sensing offers the potential to increase the speed of wavefront acquisition and to defray the cost of SHWFS devices.

© 2014 Optical Society of America

OCIS Codes
(090.1000) Holography : Aberration compensation
(100.2000) Image processing : Digital image processing
(330.7327) Vision, color, and visual optics : Visual optics, ophthalmic instrumentation
(110.7348) Imaging systems : Wavefront encoding
(110.1080) Imaging systems : Active or adaptive optics

ToC Category:
Imaging Systems

Original Manuscript: December 2, 2013
Revised Manuscript: January 17, 2014
Manuscript Accepted: January 18, 2014
Published: February 21, 2014

Virtual Issues
Vol. 9, Iss. 5 Virtual Journal for Biomedical Optics

James Polans, Ryan P. McNabb, Joseph A. Izatt, and Sina Farsiu, "Compressed wavefront sensing," Opt. Lett. 39, 1189-1192 (2014)

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