The accuracy of the estimation of optical aberrations by measuring the distorted wave front using a Hartmann-Shack
wave front sensor (HSWS) is mainly dependent upon the measurement accuracy of the centroid of the focal spot. The
most commonly used methods for centroid estimation such as the brightest spot centroid; first moment centroid;
weighted center of gravity and intensity weighted center of gravity, are generally applied on the entire individual sub-apertures
of the lens let array. However, these processes of centroid estimation are sensitive to the influence of
reflections, scattered light, and noise; especially in the case where the signal spot area is smaller compared to the whole
sub-aperture area. In this paper, we give a comparison of performance of the commonly used centroiding methods on
estimation of optical aberrations, with and without the use of some pre-processing steps (thresholding, Gaussian
smoothing and adaptive windowing). As an example we use the aberrations of the human eye model. This is done using
the raw data collected from a custom made ophthalmic aberrometer and a model eye to emulate myopic and hyper-metropic
defocus values up to 2 Diopters. We show that the use of any simple centroiding algorithm is sufficient in the
case of ophthalmic applications for estimating aberrations within the typical clinically acceptable limits of a quarter
Diopter margins, when certain pre-processing steps to reduce the impact of external factors are used.
Python is an easy open source software that can be used to simulate various optical phenomena. We have developed a suite of programs, covering both geometrical and physical optics. These simulations follow the experimental modules used in the ALOP (Active Learning in Optics and Photonics) UNESCO program in the sense that they complement it and help with student prediction of results. We present these programs and the student reactions to these simulations.