Reconstruction of the point-spread function of the human eye from two double-pass retinal images by phase-retrieval algorithms

Abstract

In the double-pass technique used to measure the optical performance of the eye, the double-pass image is the cross correlation of the input spread function with the output spread function [J. Opt. Soc. Am. A 12, 195 (1995)]. When entrance and exit pupil sizes are equal, the information on the point-spread function is lost from the double-pass image, although the modulation transfer function of the eye is obtained. A modification of the double-pass technique that uses unequal-sized entrance and exit pupils allows a low-resolution version of the ocular point-spread function to be recorded [J. Opt. Soc. Am. A 12, 2358 (1995)]. We propose the combined use of these two double-pass measurements as input in a phase-retrieval procedure to reconstruct the ocular point-spread function. We use an adapted version of the iterative Fourier-transform algorithm consisting of two steps. In the first step, error-reduction iterations with expanding weighting functions in the Fourier domain yield an estimation of the phase that serves as an initial guess for the second step, which consists of cycles of hybrid input–output iterations. We tested the robustness and limitations of the retrieval algorithm by using simulated data with and without noise. We then applied the procedure to reconstruct the point-spread function from actual measurements of double-pass retinal images in the living eye.