Generalized method for sorting Shack-Hartmann spot patterns using local similarity

Smith, Daniel G.; Greivenkamp, John E.

doi:10.1364/ao.47.004548

Cited by 19 publications

(9 citation statements)

References 8 publications

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“…9,10,12 For each algorithm, it is assumed that the spot positions are already known via some image processing method, and that the only remaining problem is the assignment of the spots to their corresponding lenslets. Figure 1 depicts the order in which spots are located for each algorithm.…”

Section: Methods-the Algorithmsmentioning

confidence: 99%

Comparison of sorting algorithms to increase the range of Hartmann-Shack aberrometry

Bedggood

Metha

2010

J. Biomed. Opt.

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Abstract. Recently many software-based approaches have been suggested for improving the range and accuracy of Hartmann-Shack aberrometry. We compare the performance of four representative algorithms, with a focus on aberrometry for the human eye. Algorithms vary in complexity from the simplistic traditional approach to iterative spline extrapolation based on prior spot measurements. Range is assessed for a variety of aberration types in isolation using computer modeling, and also for complex wavefront shapes using a real adaptive optics system. The effects of common sources of error for ocular wavefront sensing are explored. The results show that the simplest possible iterative algorithm produces comparable range and robustness compared to the more complicated algorithms, while keeping processing time minimal to afford real-time analysis. C 2010 Society of Photo-Optical Instrumentation Engineers.

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Section: Methods-the Algorithmsmentioning

confidence: 99%

Comparison of sorting algorithms to increase the range of Hartmann-Shack aberrometry

Bedggood

Metha

2010

J. Biomed. Opt.

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“…However, if the input wavafront carries some aberrations, the light spots on the focal plane present certain offset displacements from their ideal spots. Thus, by measuring the displacements of each focal point from their ideal positions, the input wavefront can be retrieved by implementing proper numerical algorithms [37][38][39].…”

Section: Self-calibration Of the Lcos Screen Surface By Using A Micromentioning

confidence: 99%

“…First, the split-lens configuration provides the phase-voltage look-up table even in presence of time-fluctuations of the phase phenomenon, as we are dealing with an interferometric system, and the required average phase is determined as a function of the applied voltage. Second, both the phase-voltage performance and the phase profile of the display can be acquired within the same optical arrangement by generating two diffractive lens configurations (split lens schemes [11] or Shack-Hartmann configurations [34,38,39]) on the same LCoS display. Third, the LCoS features can be self-retrieved without the implementation of any external calibrating set-ups (as it is the common case), which leads to a more compact system.…”

Section: Introductionmentioning

confidence: 99%

Self-addressed diffractive lens schemes for the characterization of LCoS displays

Zhang

Lizana

Iemmi

et al. 2018

Emerging Liquid Crystal Technologies XIII

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We proposed a self-calibration method to calibrate both the phase-voltage look-up table and the screen phase distribution of Liquid Crystal on Silicon (LCoS) displays by implementing different lens configurations on the studied device within a same optical scheme. On the one hand, the phase-voltage relation is determined from interferometric measurements, which are obtained by addressing split-lens phase distributions on the LCoS display. On the other hand, the surface profile is retrieved by self-addressing a diffractive micro-lens array to the LCoS display, in a way that we configure a Shack-Hartmann wavefront sensor that self-determines the screen spatial variations. Moreover, both the phase-voltage response and the surface phase inhomogeneity of the LCoS are measured within the same experimental set-up, without the necessity of further adjustments. Experimental results prove the usefulness of the above-mentioned technique for LCoS displays characterization.

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“…Once the location of that central hexagon is identified, successive identification of additional spots can be performed. For example, [25] described a method for identifying and sorting spots in a hexagonal Shack–Hartmann grid. This method can effectively sort out the spots and was adopted in this paper.…”

Section: Optical Designmentioning

confidence: 99%

Design, fabrication, and testing of a Shack–Hartmann sensor with an automatic registration feature

Zhou

Raasch

2016

Appl. Opt.

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In this research, design, construction, and testing of an innovative Shack–Hartmann sensor are described. As the most critical component, a polymer microlens array is injection molded and mounted on a board-level CMOS camera such that the focal plane of the microlens array is on the camera’s image plane. To allow for automatic registration of the spots of the measured area, a diffusing surface was created at the center of the lens array in the same diamond machining process in an uninterrupted operation. This unique diffusing surface does not generate an image spot. The no-spot feature functions as the reference in the measurement on the camera’s image plane. Using this unique feature, large global tip-tilt error can be detected and eliminated. In this research, both experiments and simulation have shown that the Shack–Hartmann sensor built using low cost components is capable of precision wavefront detection. This research also demonstrated that automatic registration based on the diffusing surface is simple and reliable.

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Generalized method for sorting Shack-Hartmann spot patterns using local similarity

Cited by 19 publications

References 8 publications

Comparison of sorting algorithms to increase the range of Hartmann-Shack aberrometry

Comparison of sorting algorithms to increase the range of Hartmann-Shack aberrometry

Self-addressed diffractive lens schemes for the characterization of LCoS displays

Design, fabrication, and testing of a Shack–Hartmann sensor with an automatic registration feature

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