Fast autofocus of microscopy images based on Depth-from-Defocus

Abstract

Microscopic computer vision differs significantly from macroscale computer vision. Autofocusing techniques is of fundamental importance to automated micromanipulation in providing high level task understanding, task planning and real time control. Depth-from-Focus (DFF) based autofocusing method is widely used in many microscope systems, while the low efficiency limited its application in micromanipulation system which needs fast autofocus for real time control. In this paper, Depth-From-Defocus (DFD) algorithms are proposed to improve autofocusing performance and robustness for microscopic optics. Two different schemes based on look-up table and function relation are investigated and evaluated through actual experiments. Experimental results validate the performances of the two proposed autofocusing methods.