Increasing the stability of the estimation of phase wavefront aberration distribution function through nonlinear adaptive filtering

Abstract

Small amounts of aberration can strongly influence optical systems' performance. Thus, reducing the noise in the process of estimating the aberration distribution function is of prime importance. This article provides a solution for nonlinear adaptive filtering of wavelet coefficients with the aim of increasing the stability of the estimation process of phase aberration distribution function. It should be noted that the estimation process is based on the wavelet profilometry. The basic idea in this technique is based on the assumption that noise spectrum is widely distributed with small amounts. Thus, using nonlinear filtering may increase the stability of the extraction process of aberration function's parameters. Considering the importance of determining the true threshold, based on the correlation of third-order cumulants, a new utility function is defined. Using this function, it is expected that the threshold would adapt itself to its optimum value. Simulation results confirmed the accuracy and efficiency of the proposed solution.