Wavefront reconstruction from tangential and sagittal curvature

In a previous contribution [Appl. Opt. 51, 8599 (2012)], a coauthor of this work presented a method for reconstructing the wavefront aberration from tangential refractive power data measured using dynamic skiascopy. Here we propose a new regularized least squares method where the wavefront is reconstructed not only using tangential but also sagittal curvature data. We prove that our new method provides improved quality reconstruction for typical and also for highly aberrated wavefronts, under a wide range of experimental error levels. Our method may be applied to any type of wavefront sensor (not only dynamic skiascopy) able to measure either just tangential or tangential plus sagittal curvature data.

Robust fitting of Zernike polynomials to noisy point clouds defined over connected domains of arbitrary shape

A new method for fitting a series of Zernike polynomials to point clouds defined over connected domains of arbitrary shape defined within the unit circle is presented in this work. The method is based on the application of machine learning fitting techniques by constructing an extended training set in order to ensure the smooth variation of local curvature over the whole domain. Therefore this technique is best suited for fitting points corresponding to ophthalmic lenses surfaces, particularly progressive power ones, in non-regular domains. We have tested our method by fitting numerical and real surfaces reaching an accuracy of 1 micron in elevation and 0.1 D in local curvature in agreement with the customary tolerances in the ophthalmic manufacturing industry.