Unwrapping Hartmann-Shack images from highly aberrated eyes using an iterative B-spline based extrapolation method.

PURPOSE

When the wavefront aberrations of the eye are measured with a Hartmann-Shack (HS) sensor, the resulting spot pattern must be unwrapped, that is, for each lenslet the corresponding spot must be identified. This puts a limitation on the measurable amount of aberrations. To extend the range of an HS sensor, a powerful unwrapping algorithm has been developed.

METHODS

The unwrapping algorithm starts by connecting the central HS spots to the central lenslets. It then fits a B-spline function through a least squares estimate to the deviations of the central HS spots. This function is then extrapolated to find the expected locations of HS spots for the unconnected lenslets. The extrapolation is performed gradually in an iterative manner; the closest unconnected lenslets are extrapolated and connected, and then the B-spline function is least squares fitted to all connected HS spots and extrapolated again.

RESULTS

Wavefront aberrations from eyes with high aberrations can be successfully unwrapped with the developed algorithm. The dynamic range of a typical HS sensor increases 3.5 to 13 times compared with a simple unwrapping algorithm.

CONCLUSIONS

The implemented algorithm is an efficient unwrapping tool and allows the use of lenslets with a low numerical aperture and thus gives a relatively higher accuracy of measurements of the ocular aberrations.