Fast Autofocusing Algorithm Based on Variable Step Search and Curve Fitting Applied in the Near- and Far-Field Detection System With a Common Optical Path

Abstract

We design a set of near- and far-field detection system with a common optical path. And we propose a fast autofocusing algorithm based on variable step search and curve fitting for defocus aberration correction of the system. By denoising the image with the image processing method, improving the traditional hill-climbing search method with variable step search and curve fitting, and taking the sum of the squares of grayscale differences and the image similarity function as criteria, we effectively improve the speed and accuracy of autofocus. The theoretical positioning accuracy reaches 0.076 μm, the code statement frequency count of the algorithm is reduced by 2MN times, and the resolution enhances from 28.51 lp mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−1</sup> to 71.8 lp mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−1</sup> . Numerical simulations and experimental results have validated the effectiveness of the proposed method.