Calculating Zernike coefficients from Fourier coefficients

1. A method of determining an optical surface model for an optical tissue system of an eye, the method comprising:

inputting a Fourier transform of optical data from the optical tissue system;

inputting a conjugate Fourier transform of a basis function surface;

determining a Fourier domain sum of the Fourier transform and the conjugate Fourier transform;

calculating an estimated basis function coefficient based on the Fourier domain sum; and

determining the optical surface model based on the estimated basis function coefficient.

2. The method of claim 1 , wherein the Fourier transform comprises an iterative Fourier transform.

3. The method of claim 1 , wherein the basis function surface comprises a Zernike polynomial surface and the estimated basis function coefficient comprises an estimated Zernike polynomial coefficient.

4. The method of claim 3 , wherein the estimated Zernike polynomial coefficient comprises a member selected from the group consisting of a low order aberration term and a high order aberration term.

5. The method of claim 3 , wherein the estimated Zernike polynomial coefficient comprises a member selected from the group consisting of a sphere term, a cylinder term, a coma term, and a spherical aberration term.

6. The method of claim 1 , wherein the basis function surface comprises a Fourier series surface and the estimated basis function coefficient comprises an estimated Fourier series coefficient.

7. The method of claim 1 , wherein the basis function surface comprises a Taylor monomial surface and the estimated basis function coefficient comprises an estimated Taylor monomial coefficient.

8. The method of claim 1 , wherein the optical data is derived from a wavefront map of the optical system.

9. The method of claim 1 , wherein the optical data comprises nondiscrete data.

10. The method of claim 1 , wherein the optical data comprises a set of N×N discrete grid points, and the Fourier transform and the conjugate transform are in a numerical format.

11. The method of claim 1 , wherein the optical data comprises a set of N×N discrete grid points, and the Fourier transform and the conjugate transform are in an analytical format.

12. The method of claim 11 , wherein a y-axis separation distance between each neighboring grid point is 0.5 and an x-axis separation distance between each neighboring grid point is 0.5.

13. A system for calculating an estimated basis function coefficient for an optical tissue system of an eye, the system comprising:

a) a light source for transmitting an image through the optical tissue system;

b) a sensor oriented for determining a set of local gradients for the optical tissue system by detecting the transmitted image;

c) a processor coupled with the sensor; and

d) a memory coupled with the processor, the memory configured to store a plurality of code modules for execution by the processor, the plurality of code modules comprising:

i) a module for inputting a Fourier transform of the set of local gradients for the optical tissue system;

ii) a module for inputting a conjugate Fourier transform of a basis function surface;

iii) a module for determining a Fourier domain sum of the Fourier transform and the conjugate Fourier transform; and

iv) a module for calculating the estimated basis function coefficient based on the Fourier domain sum.

14. The system of claim 13 , wherein the basis function surface comprises a member selected from the group consisting of a Zernike polynomial surface, a Fourier series surface, and a Taylor monomial surface.

15. The system of claim 13 , wherein the optical tissue system of the eye is represented by a two dimensional surface comprising a set of N×N discrete grid points, and the Fourier transform and the conjugate transform are in a numerical format.

16. The system of claim 13 , wherein the optical tissue system of the eye is represented by a two dimensional surface comprising a set of N×N discrete grid points, the Fourier transform and the conjugate transform are in an analytical format, a y-axis separation distance between each neighboring grid point is 0.5, and an x-axis separation distance between each neighboring grid point is 0.5.