Confocal signal evaluation algorithms for surface metrology: uncertainty and numerical efficiency.

Abstract

Confocal microscopy is one of the dominating measurement techniques in surface metrology, with an enhanced lateral resolution compared to alternative optical methods. However, the axial resolution in confocal microscopy is strongly dependent on the accuracy of signal evaluation algorithms, which are limited by random noise. Here, we discuss the influence of various noise sources on confocal intensity signal evaluating algorithms, including center-of-mass, parabolic least-square fit, and cross-correlation-based methods. We derive results in closed form for the uncertainty in height evaluation on surface microstructures, also accounting for the number of axially measured intensity values and a threshold that is commonly applied before signal evaluation. The validity of our results is verified by numerical Monte Carlo simulations. In addition, we implemented all three algorithms and analyzed their numerical efficiency. Our results can serve as guidance for a suitable choice of measurement parameters in confocal surface topography measurement, and thus lead to a shorter measurement time in practical applications.