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Local sharpening and subspace wavefront correction with predictive dynamic digital holography
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Paper Abstract

Digital holography holds several advantages over conventional imaging and wavefront sensing, chief among these being significantly fewer and simpler optical components and the retrieval of complex field. Consequently, many imaging and sensing applications including microscopy and optical tweezing have turned to using digital holography. A significant obstacle for digital holography in real-time applications, such as wavefront sensing for high energy laser systems and high speed imaging for target racking, is the fact that digital holography is computationally intensive; it requires iterative virtual wavefront propagation and hill-climbing to optimize some sharpness criteria. It has been shown recently that minimum-variance wavefront prediction can be integrated with digital holography and image sharpening to reduce significantly large number of costly sharpening iterations required to achieve near-optimal wavefront correction. This paper demonstrates further gains in computational efficiency with localized sharpening in conjunction with predictive dynamic digital holography for real-time applications. The method optimizes sharpness of local regions in a detector plane by parallel independent wavefront correction on reduced-dimension subspaces of the complex field in a spectral plane.

Paper Details

Date Published: 6 September 2017
PDF: 10 pages
Proc. SPIE 10410, Unconventional and Indirect Imaging, Image Reconstruction, and Wavefront Sensing 2017, 104100F (6 September 2017); doi: 10.1117/12.2284435
Show Author Affiliations
Sennan Sulaiman, Univ. of California, Los Angeles (United States)
Steve Gibson, Univ. of California, Los Angeles (United States)


Published in SPIE Proceedings Vol. 10410:
Unconventional and Indirect Imaging, Image Reconstruction, and Wavefront Sensing 2017
Jean J. Dolne; Rick P. Millane, Editor(s)

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