April 2009
Volume 50, Issue 13
ARVO Annual Meeting Abstract  |   April 2009
Predicting Depth of Focus With Image Quality Metrics
Author Affiliations & Notes
  • A. L. Hickenbotham
    Univ of California - Berkeley, Berkeley, California
  • R. A. Applegate
    Optometry, Univ of Houston, Houston, Texas
  • A. Roorda
    Univ of California - Berkeley, Berkeley, California
  • Footnotes
    Commercial Relationships  A.L. Hickenbotham, None; R.A. Applegate, None; A. Roorda, None.
  • Footnotes
    Support  K12 EY017269 (ALH), R01 EY08520 (RAA), R01-EY05109 (LNT), and P30 EY07551(UHCO)
Investigative Ophthalmology & Visual Science April 2009, Vol.50, 1119. doi:
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    • Get Citation

      A. L. Hickenbotham, R. A. Applegate, A. Roorda; Predicting Depth of Focus With Image Quality Metrics. Invest. Ophthalmol. Vis. Sci. 2009;50(13):1119.

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      © ARVO (1962-2015); The Authors (2016-present)

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Purpose: : To predict depth of focus using image quality metrics.

Methods: : We performed a random choice visual acuity (VA) experiment using 20 Snellen letters presented on an 11-bit display monitor. Letters were convolved with the PSF of 0.25µm step Zernike aberrations (c7, c9, c12, c24, and c40) and 0.25 D defocus steps for a 5 mm pupil. VA for each PSF was measured with 5 letters for each letter size, which ranged from 20/20 and smaller but were magnified, after blurring, to 20/200 to decouple the size aspect (minimizing effects of viewer’s aberrations, negating photoreceptor spacing, and avoiding retinal sampling errors).Correlation of VA values over the range of conditions was tested against 31 different metrics of image quality (as defined by Thibos, Hong, Bradley, & Applegate) (2004). J.Vis, 4(4), 322-328) using GetMetrics software provided by Larry Thibos and Ray Applegate. These metrics were further optimized using statistical regression to increase correlation with VA. Depth of focus (DOF) was determined by a summation of defocus values that presented acuities of -0.3 logMAR or better.

Results: : Decoupling size from blur resulted in higher VA than standard testing due to an absence of limiting factors such as retinal sampling errors and photoreceptor spacing. Spherical aberrations (4th, 6th, and 8th order), coma, and trefoil reduced VA and increased DOF. PFSt (Pupil fraction using tessellation) and VOTF (OTF volume normalized by MTF volume) were found to be the best predictors of VA (r=0.61 and 0.58 respectively) of the 31 image quality metrics. A best-fit equation using sqrt PFSt and VOTF^2 was found to have a correlation of r=0.76 with measured visual acuity. This same linear formula had a correlation of r=0.75 with measured DOF.

Conclusions: : A combination of size-decoupled VA testing and image quality metrics can be used to find aberration profiles that enhance depth of focus while retaining good visual acuity. This pre-selection of optimal profiles provides an efficient approach to the ultimate goal of performing more realistic testing in an adaptive optics system.

Keywords: aberrations • depth • presbyopia 

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