A novel cubic-exp evaluation algorithm considering non-symmetrical axial response signals of confocal microscopes

The depth discrimination in confocal microscopy is based on the digital analysis of depth response signals obtained by each camera pixel during measurement. Various signal-processing algorithms are used for this purpose. The accuracy of these algorithms is inter alia restricted by the axial symmetry of the signals. However, in practice response signals are rather asymmetrical especially in case of measurement objects with critical surface structures such as edges or steep flanks. We present a novel signal-processing algorithm based on an exponential function with a cubic argument to handle asymmetrical and also symmetrical depth response signals. Results obtained by this algorithm are compared to those of commonly used signal processing algorithms. It turns out that the novel algorithm is more robust, more accurate and exhibits a repeatability of a similar order compared to other algorithms. RESEARCH HIGHLIGHTS: A novel, more robust algorithm with improved accuracy in peak extraction especially for asymmetrical response signals in confocal microscopy is introduced and validated. Improved accuracy is demonstrated for height and layer thickness measurements.